From a79e2dc7fbb2c0f9022ea758df1c5d45185d67a6 Mon Sep 17 00:00:00 2001 From: Kaiyu Xie <26294424+kaiyux@users.noreply.github.com> Date: Tue, 25 Nov 2025 03:40:39 +0000 Subject: [PATCH] Update GitHub pages in root to v1.2.0rc4 --- .buildinfo | 2 +- _cpp_gen/executor.html | 8 ++--- _cpp_gen/runtime.html | 8 ++--- .../attention.py | 19 ++++-------- .../model_engine.py | 7 +++-- _modules/index.html | 8 ++--- _modules/tensorrt_llm/builder.html | 8 ++--- .../tensorrt_llm/disaggregated_params.html | 8 ++--- _modules/tensorrt_llm/executor/request.html | 8 ++--- _modules/tensorrt_llm/executor/result.html | 8 ++--- _modules/tensorrt_llm/executor/utils.html | 8 ++--- _modules/tensorrt_llm/functional.html | 8 ++--- _modules/tensorrt_llm/layers/activation.html | 8 ++--- _modules/tensorrt_llm/layers/attention.html | 8 ++--- _modules/tensorrt_llm/layers/cast.html | 8 ++--- _modules/tensorrt_llm/layers/conv.html | 8 ++--- _modules/tensorrt_llm/layers/embedding.html | 8 ++--- _modules/tensorrt_llm/layers/linear.html | 8 ++--- _modules/tensorrt_llm/layers/mlp.html | 8 ++--- .../tensorrt_llm/layers/normalization.html | 8 ++--- _modules/tensorrt_llm/layers/pooling.html | 8 ++--- _modules/tensorrt_llm/llmapi/build_cache.html | 8 ++--- _modules/tensorrt_llm/llmapi/llm.html | 13 ++++---- _modules/tensorrt_llm/llmapi/llm_args.html | 11 +++---- _modules/tensorrt_llm/llmapi/mm_encoder.html | 8 ++--- _modules/tensorrt_llm/llmapi/mpi_session.html | 8 ++--- .../tensorrt_llm/models/baichuan/model.html | 8 ++--- _modules/tensorrt_llm/models/bert/model.html | 8 ++--- _modules/tensorrt_llm/models/bloom/model.html | 8 ++--- .../tensorrt_llm/models/chatglm/config.html | 8 ++--- .../tensorrt_llm/models/chatglm/model.html | 8 ++--- _modules/tensorrt_llm/models/clip/model.html | 8 ++--- .../tensorrt_llm/models/cogvlm/config.html | 8 ++--- .../tensorrt_llm/models/cogvlm/model.html | 8 ++--- .../tensorrt_llm/models/commandr/model.html | 8 ++--- _modules/tensorrt_llm/models/dbrx/config.html | 8 ++--- _modules/tensorrt_llm/models/dbrx/model.html | 8 ++--- .../models/deepseek_v1/model.html | 8 ++--- .../models/deepseek_v2/model.html | 8 ++--- _modules/tensorrt_llm/models/dit/model.html | 8 ++--- _modules/tensorrt_llm/models/eagle/model.html | 8 ++--- .../tensorrt_llm/models/enc_dec/model.html | 8 ++--- .../tensorrt_llm/models/falcon/config.html | 8 ++--- .../tensorrt_llm/models/falcon/model.html | 8 ++--- .../tensorrt_llm/models/gemma/config.html | 8 ++--- _modules/tensorrt_llm/models/gemma/model.html | 8 ++--- _modules/tensorrt_llm/models/gpt/config.html | 8 ++--- _modules/tensorrt_llm/models/gpt/model.html | 8 ++--- _modules/tensorrt_llm/models/gptj/config.html | 8 ++--- _modules/tensorrt_llm/models/gptj/model.html | 8 ++--- .../tensorrt_llm/models/gptneox/model.html | 8 ++--- .../tensorrt_llm/models/llama/config.html | 8 ++--- _modules/tensorrt_llm/models/llama/model.html | 8 ++--- _modules/tensorrt_llm/models/mamba/model.html | 8 ++--- .../tensorrt_llm/models/medusa/config.html | 8 ++--- .../tensorrt_llm/models/medusa/model.html | 8 ++--- .../tensorrt_llm/models/mllama/model.html | 8 ++--- .../tensorrt_llm/models/mmdit_sd3/model.html | 8 ++--- .../tensorrt_llm/models/modeling_utils.html | 8 ++--- _modules/tensorrt_llm/models/mpt/model.html | 8 ++--- .../models/multimodal_encoders/config.html | 8 ++--- .../models/multimodal_encoders/model.html | 8 ++--- _modules/tensorrt_llm/models/opt/model.html | 8 ++--- _modules/tensorrt_llm/models/phi/model.html | 8 ++--- _modules/tensorrt_llm/models/phi3/model.html | 8 ++--- .../models/recurrentgemma/model.html | 8 ++--- .../tensorrt_llm/models/redrafter/model.html | 8 ++--- _modules/tensorrt_llm/plugin/plugin.html | 8 ++--- _modules/tensorrt_llm/quantization/mode.html | 8 ++--- .../quantization/quantize_by_modelopt.html | 8 ++--- .../runtime/enc_dec_model_runner.html | 8 ++--- _modules/tensorrt_llm/runtime/generation.html | 8 ++--- .../runtime/kv_cache_manager.html | 8 ++--- .../tensorrt_llm/runtime/model_runner.html | 8 ++--- .../runtime/model_runner_cpp.html | 8 ++--- .../runtime/multimodal_model_runner.html | 8 ++--- _modules/tensorrt_llm/runtime/session.html | 8 ++--- _modules/tensorrt_llm/sampling_params.html | 8 ++--- .../run-benchmark-with-trtllm-serve.md.txt | 2 +- ...ent-guide-for-deepseek-r1-on-trtllm.md.txt | 2 +- ...loyment-guide-for-gpt-oss-on-trtllm.md.txt | 2 +- ...nt-guide-for-llama3.3-70b-on-trtllm.md.txt | 2 +- ...nt-guide-for-llama4-scout-on-trtllm.md.txt | 2 +- _sources/examples/curl_chat_client.rst.txt | 2 +- .../curl_chat_client_for_multimodal.rst.txt | 2 +- .../examples/curl_completion_client.rst.txt | 2 +- .../deepseek_r1_reasoning_parser.rst.txt | 2 +- _sources/examples/genai_perf_client.rst.txt | 2 +- .../genai_perf_client_for_multimodal.rst.txt | 2 +- _sources/examples/llm_guided_decoding.rst.txt | 2 +- _sources/examples/llm_inference.rst.txt | 2 +- _sources/examples/llm_inference_async.rst.txt | 2 +- .../llm_inference_async_streaming.rst.txt | 2 +- .../llm_inference_distributed.rst.txt | 2 +- .../examples/llm_kv_cache_connector.rst.txt | 2 +- .../examples/llm_kv_cache_offloading.rst.txt | 2 +- .../examples/llm_logits_processor.rst.txt | 2 +- .../examples/llm_mgmn_llm_distributed.rst.txt | 2 +- .../examples/llm_mgmn_trtllm_bench.rst.txt | 2 +- .../examples/llm_mgmn_trtllm_serve.rst.txt | 2 +- _sources/examples/llm_multilora.rst.txt | 2 +- _sources/examples/llm_runtime.rst.txt | 2 +- _sources/examples/llm_sampling.rst.txt | 2 +- .../examples/llm_sparse_attention.rst.txt | 2 +- .../examples/llm_speculative_decoding.rst.txt | 2 +- _sources/examples/openai_chat_client.rst.txt | 2 +- .../openai_chat_client_for_multimodal.rst.txt | 2 +- .../examples/openai_completion_client.rst.txt | 2 +- .../openai_completion_client_for_lora.rst.txt | 2 +- ...enai_completion_client_json_schema.rst.txt | 2 +- _sources/llm-api/reference.rst.txt | 4 +-- _sources/quick-start-guide.md.txt | 2 +- ...actice_on_DeepSeek-R1_in_TensorRT-LLM.html | 8 ++--- blogs/Falcon180B-H200.html | 8 ++--- blogs/H100vsA100.html | 8 ++--- blogs/H200launch.html | 8 ++--- blogs/XQA-kernel.html | 8 ++--- blogs/quantization-in-TRT-LLM.html | 8 ++--- .../blog10_ADP_Balance_Strategy.html | 8 ++--- blogs/tech_blog/blog11_GPT_OSS_Eagle3.html | 8 ++--- ...ded_Decoding_and_Speculative_Decoding.html | 8 ++--- ...ompute_Implementation_in_TensorRT-LLM.html | 8 ++--- ...ert_Parallelism_in_TensorRT-LLM_part3.html | 8 ++--- ...ek-R1_Performance_on_NVIDIA_B200_GPUs.html | 8 ++--- ...1_MTP_Implementation_and_Optimization.html | 8 ++--- ...1_Throughput_on_NVIDIA_Blackwell_GPUs.html | 8 ++--- ...ng_Expert_Parallelism_in_TensorRT-LLM.html | 8 ++--- ...Disaggregated_Serving_in_TensorRT-LLM.html | 8 ++--- .../blog6_Llama4_maverick_eagle_guide.html | 8 ++--- ...formance_Analysis_And_Auto_Enablement.html | 8 ++--- ...ert_Parallelism_in_TensorRT-LLM_part2.html | 8 ++--- .../blog9_Deploying_GPT_OSS_on_TRTLLM.html | 8 ++--- commands/trtllm-bench.html | 8 ++--- commands/trtllm-build.html | 8 ++--- commands/trtllm-eval.html | 8 ++--- commands/trtllm-serve/index.html | 8 ++--- .../run-benchmark-with-trtllm-serve.html | 10 +++---- commands/trtllm-serve/trtllm-serve.html | 14 ++++++--- ...yment-guide-for-deepseek-r1-on-trtllm.html | 10 +++---- ...eployment-guide-for-gpt-oss-on-trtllm.html | 10 +++---- ...ment-guide-for-llama3.3-70b-on-trtllm.html | 10 +++---- ...ment-guide-for-llama4-scout-on-trtllm.html | 10 +++---- ...oyment-guide-for-qwen3-next-on-trtllm.html | 8 ++--- deployment-guide/index.html | 8 ++--- developer-guide/api-change.html | 8 ++--- developer-guide/ci-overview.html | 8 ++--- developer-guide/dev-containers.html | 8 ++--- developer-guide/kv-transfer.html | 8 ++--- developer-guide/overview.html | 8 ++--- developer-guide/perf-analysis.html | 8 ++--- developer-guide/perf-benchmarking.html | 8 ++--- developer-guide/perf-overview.html | 12 ++++---- examples/curl_chat_client.html | 10 +++---- examples/curl_chat_client_for_multimodal.html | 10 +++---- examples/curl_completion_client.html | 10 +++---- examples/customization.html | 8 ++--- examples/deepseek_r1_reasoning_parser.html | 10 +++---- examples/dynamo_k8s_example.html | 8 ++--- examples/genai_perf_client.html | 10 +++---- .../genai_perf_client_for_multimodal.html | 10 +++---- examples/index.html | 8 ++--- examples/kvcacheconfig.html | 8 ++--- examples/kvcacheretentionconfig.html | 8 ++--- examples/llm_api_examples.html | 8 ++--- examples/llm_guided_decoding.html | 10 +++---- examples/llm_inference.html | 10 +++---- examples/llm_inference_async.html | 10 +++---- examples/llm_inference_async_streaming.html | 10 +++---- examples/llm_inference_distributed.html | 10 +++---- examples/llm_kv_cache_connector.html | 10 +++---- examples/llm_kv_cache_offloading.html | 10 +++---- examples/llm_logits_processor.html | 10 +++---- examples/llm_mgmn_llm_distributed.html | 10 +++---- examples/llm_mgmn_trtllm_bench.html | 10 +++---- examples/llm_mgmn_trtllm_serve.html | 10 +++---- examples/llm_multilora.html | 10 +++---- examples/llm_runtime.html | 10 +++---- examples/llm_sampling.html | 10 +++---- examples/llm_sparse_attention.html | 10 +++---- examples/llm_speculative_decoding.html | 10 +++---- examples/openai_chat_client.html | 10 +++---- .../openai_chat_client_for_multimodal.html | 10 +++---- examples/openai_completion_client.html | 10 +++---- .../openai_completion_client_for_lora.html | 10 +++---- .../openai_completion_client_json_schema.html | 10 +++---- examples/trtllm_serve_examples.html | 8 ++--- features/additional-outputs.html | 8 ++--- features/attention.html | 10 +++---- .../benchmarking_with_trtllm_bench.html | 8 ++--- .../auto_deploy/advanced/example_run.html | 8 ++--- .../advanced/expert_configurations.html | 8 ++--- features/auto_deploy/advanced/logging.html | 8 ++--- features/auto_deploy/advanced/workflow.html | 8 ++--- features/auto_deploy/auto-deploy.html | 8 ++--- features/auto_deploy/support_matrix.html | 8 ++--- features/checkpoint-loading.html | 8 ++--- features/disagg-serving.html | 8 ++--- features/feature-combination-matrix.html | 8 ++--- features/kvcache.html | 8 ++--- features/long-sequence.html | 8 ++--- features/lora.html | 8 ++--- features/multi-modality.html | 12 ++++---- features/overlap-scheduler.html | 8 ++--- features/paged-attention-ifb-scheduler.html | 12 ++++---- features/parallel-strategy.html | 8 ++--- features/quantization.html | 8 ++--- features/ray-orchestrator.html | 8 ++--- features/sampling.html | 18 +++++------ features/speculative-decoding.html | 8 ++--- ...orch_compile_and_piecewise_cuda_graph.html | 8 ++--- genindex.html | 16 ++++++---- index.html | 8 ++--- installation/build-from-source-linux.html | 10 +++---- installation/containers.html | 10 +++---- installation/index.html | 8 ++--- installation/linux.html | 8 ++--- legacy/advanced/disaggregated-service.html | 8 ++--- legacy/advanced/executor.html | 18 +++++------ legacy/advanced/expert-parallelism.html | 8 ++--- legacy/advanced/gpt-attention.html | 12 ++++---- legacy/advanced/gpt-runtime.html | 8 ++--- legacy/advanced/graph-rewriting.html | 8 ++--- legacy/advanced/kv-cache-management.html | 8 ++--- legacy/advanced/kv-cache-reuse.html | 8 ++--- legacy/advanced/lora.html | 8 ++--- .../advanced/lowprecision-pcie-allreduce.html | 8 ++--- .../open-sourced-cutlass-kernels.html | 8 ++--- legacy/advanced/speculative-decoding.html | 8 ++--- legacy/advanced/weight-streaming.html | 8 ++--- legacy/architecture/add-model.html | 8 ++--- legacy/architecture/checkpoint.html | 8 ++--- legacy/architecture/core-concepts.html | 18 +++++------ legacy/architecture/model-weights-loader.html | 8 ++--- legacy/architecture/workflow.html | 8 ++--- .../build-image-to-dockerhub.html | 8 ++--- legacy/dev-on-cloud/dev-on-runpod.html | 8 ++--- legacy/key-features.html | 8 ++--- legacy/performance/perf-analysis.html | 8 ++--- legacy/performance/perf-benchmarking.html | 8 ++--- .../benchmarking-default-performance.html | 8 ++--- .../deciding-model-sharding-strategy.html | 8 ++--- .../fp8-quantization.html | 8 ++--- .../performance-tuning-guide/index.html | 8 ++--- .../introduction.html | 8 ++--- ...ing-max-batch-size-and-max-num-tokens.html | 8 ++--- .../useful-build-time-flags.html | 8 ++--- .../useful-runtime-flags.html | 8 ++--- .../python-api/tensorrt_llm.functional.html | 8 ++--- legacy/python-api/tensorrt_llm.layers.html | 8 ++--- legacy/python-api/tensorrt_llm.models.html | 8 ++--- legacy/python-api/tensorrt_llm.plugin.html | 8 ++--- .../python-api/tensorrt_llm.quantization.html | 8 ++--- legacy/python-api/tensorrt_llm.runtime.html | 8 ++--- legacy/reference/memory.html | 12 ++++---- .../multimodal-feature-support-matrix.html | 8 ++--- legacy/reference/precision.html | 28 +++++++++--------- legacy/reference/support-matrix.html | 8 ++--- legacy/reference/troubleshooting.html | 8 ++--- legacy/tensorrt_quickstart.html | 8 ++--- legacy/torch.html | 8 ++--- llm-api/index.html | 8 ++--- llm-api/reference.html | 14 ++++----- models/adding-new-model.html | 8 ++--- models/supported-models.html | 8 ++--- objects.inv | Bin 181367 -> 181378 bytes overview.html | 10 +++---- py-modindex.html | 8 ++--- quick-start-guide.html | 10 +++---- release-notes.html | 8 ++--- search.html | 8 ++--- searchindex.js | 2 +- torch/adding_new_model.html | 8 ++--- torch/arch_overview.html | 8 ++--- torch/attention.html | 8 ++--- .../benchmarking_with_trtllm_bench.html | 8 ++--- torch/auto_deploy/advanced/example_run.html | 8 ++--- .../advanced/expert_configurations.html | 8 ++--- torch/auto_deploy/advanced/logging.html | 8 ++--- .../advanced/serving_with_trtllm_serve.html | 8 ++--- torch/auto_deploy/advanced/workflow.html | 8 ++--- torch/auto_deploy/auto-deploy.html | 8 ++--- torch/auto_deploy/support_matrix.html | 8 ++--- torch/features/checkpoint_loading.html | 8 ++--- torch/features/lora.html | 8 ++--- torch/features/overlap_scheduler.html | 8 ++--- torch/features/quantization.html | 8 ++--- torch/features/sampling.html | 8 ++--- torch/kv_cache_manager.html | 8 ++--- torch/scheduler.html | 8 ++--- 289 files changed, 1140 insertions(+), 1132 deletions(-) diff --git a/.buildinfo b/.buildinfo index e1872b4a6c..f5f2f10e8a 100644 --- a/.buildinfo +++ b/.buildinfo @@ -1,4 +1,4 @@ # Sphinx build info version 1 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 5b10b2153627779ea5be4dbb07d82396 +config: e877fa21f4c01def0efb8f650d34bf16 tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/_cpp_gen/executor.html b/_cpp_gen/executor.html index 824e5f6543..366b7645cb 100644 --- a/_cpp_gen/executor.html +++ b/_cpp_gen/executor.html @@ -61,7 +61,7 @@ @@ -74,7 +74,7 @@ - + @@ -13984,9 +13984,9 @@
Last updated on November 20, 2025.
+Last updated on November 23, 2025.
-This page is generated by TensorRT-LLM commit 2128f73.
+This page is generated by TensorRT-LLM commit a761585.
k
- Last updated on November 20, 2025.
+ Last updated on November 23, 2025.
- This page is generated by TensorRT-LLM commit 2128f73.
+ This page is generated by TensorRT-LLM commit a761585.
diff --git a/blogs/tech_blog/blog8_Scaling_Expert_Parallelism_in_TensorRT-LLM_part2.html b/blogs/tech_blog/blog8_Scaling_Expert_Parallelism_in_TensorRT-LLM_part2.html
index f20fa3e2b5..57e095add2 100644
--- a/blogs/tech_blog/blog8_Scaling_Expert_Parallelism_in_TensorRT-LLM_part2.html
+++ b/blogs/tech_blog/blog8_Scaling_Expert_Parallelism_in_TensorRT-LLM_part2.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -984,9 +984,9 @@ always defer defer+madvise
- Last updated on November 20, 2025.
+ Last updated on November 23, 2025.
- This page is generated by TensorRT-LLM commit 2128f73.
+ This page is generated by TensorRT-LLM commit a761585.
diff --git a/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.html b/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.html
index 69d652b815..60ee9ec58f 100644
--- a/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.html
+++ b/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -1009,9 +1009,9 @@ others according to your needs.
diff --git a/commands/trtllm-bench.html b/commands/trtllm-bench.html
index 30a4ea067e..9076306e92 100644
--- a/commands/trtllm-bench.html
+++ b/commands/trtllm-bench.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -1339,9 +1339,9 @@
diff --git a/commands/trtllm-build.html b/commands/trtllm-build.html
index 6f37e92153..bae82c719e 100644
--- a/commands/trtllm-build.html
+++ b/commands/trtllm-build.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -1016,9 +1016,9 @@
diff --git a/commands/trtllm-eval.html b/commands/trtllm-eval.html
index 779e0ced41..573822250a 100644
--- a/commands/trtllm-eval.html
+++ b/commands/trtllm-eval.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -1436,9 +1436,9 @@ trtllm-eval --model meta-llama/Lla
diff --git a/commands/trtllm-serve/index.html b/commands/trtllm-serve/index.html
index a674de9032..d06e7bee30 100644
--- a/commands/trtllm-serve/index.html
+++ b/commands/trtllm-serve/index.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -645,9 +645,9 @@
diff --git a/commands/trtllm-serve/run-benchmark-with-trtllm-serve.html b/commands/trtllm-serve/run-benchmark-with-trtllm-serve.html
index 3f38600afc..db49675451 100644
--- a/commands/trtllm-serve/run-benchmark-with-trtllm-serve.html
+++ b/commands/trtllm-serve/run-benchmark-with-trtllm-serve.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -541,7 +541,7 @@ A complete reference for the API is available in the #
TensorRT LLM distributes the pre-built container on NGC Catalog.
You can launch the container using the following command:
-docker run --rm -it --ipc host -p 8000:8000 --gpus all --ulimit memlock=-1 --ulimit stack=67108864 nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc3
+docker run --rm -it --ipc host -p 8000:8000 --gpus all --ulimit memlock=-1 --ulimit stack=67108864 nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc4
@@ -1006,9 +1006,9 @@ trtllm-serve ${m
diff --git a/commands/trtllm-serve/trtllm-serve.html b/commands/trtllm-serve/trtllm-serve.html
index 3c0d92f60a..9f00d34205 100644
--- a/commands/trtllm-serve/trtllm-serve.html
+++ b/commands/trtllm-serve/trtllm-serve.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -906,6 +906,12 @@ Since the statistics are stored in an internal queue and removed once retrieved,
+
+-
+--custom_module_dirs <custom_module_dirs>#
+Paths to custom module directories to import.
+
+
-
--log_level <log_level>#
@@ -1235,9 +1241,9 @@ Please refer to Performance Benchmarking with `trtllm-serve <
diff --git a/deployment-guide/deployment-guide-for-deepseek-r1-on-trtllm.html b/deployment-guide/deployment-guide-for-deepseek-r1-on-trtllm.html
index 9f414e5dac..5812fe248b 100644
--- a/deployment-guide/deployment-guide-for-deepseek-r1-on-trtllm.html
+++ b/deployment-guide/deployment-guide-for-deepseek-r1-on-trtllm.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -588,7 +588,7 @@
-p 8000:8000 \
-v ~/.cache:/root/.cache:rw \
--name tensorrt_llm \
-nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc3 \
+nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc4 \
/bin/bash
@@ -1180,9 +1180,9 @@ chmod +x bench.sh
diff --git a/deployment-guide/deployment-guide-for-gpt-oss-on-trtllm.html b/deployment-guide/deployment-guide-for-gpt-oss-on-trtllm.html
index e9d57b4a7c..eed951928e 100644
--- a/deployment-guide/deployment-guide-for-gpt-oss-on-trtllm.html
+++ b/deployment-guide/deployment-guide-for-gpt-oss-on-trtllm.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -576,7 +576,7 @@
-p 8000:8000 \
-v ~/.cache:/root/.cache:rw \
--name tensorrt_llm \
-nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc3 \
+nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc4 \
/bin/bash
@@ -1140,9 +1140,9 @@ chmod +x bench.sh
diff --git a/deployment-guide/deployment-guide-for-llama3.3-70b-on-trtllm.html b/deployment-guide/deployment-guide-for-llama3.3-70b-on-trtllm.html
index b7bd83c97a..5472d7d39f 100644
--- a/deployment-guide/deployment-guide-for-llama3.3-70b-on-trtllm.html
+++ b/deployment-guide/deployment-guide-for-llama3.3-70b-on-trtllm.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -555,7 +555,7 @@ Python3 and python3-pip (Optional, for accuracy evaluation only)
-p 8000:8000 \
-v ~/.cache:/root/.cache:rw \
--name tensorrt_llm \
-nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc3 \
+nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc4 \
/bin/bash
@@ -1058,9 +1058,9 @@ chmod +x bench.sh
diff --git a/deployment-guide/deployment-guide-for-llama4-scout-on-trtllm.html b/deployment-guide/deployment-guide-for-llama4-scout-on-trtllm.html
index de6298d782..556dd06599 100644
--- a/deployment-guide/deployment-guide-for-llama4-scout-on-trtllm.html
+++ b/deployment-guide/deployment-guide-for-llama4-scout-on-trtllm.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -557,7 +557,7 @@
-p 8000:8000 \
-v ~/.cache:/root/.cache:rw \
--name tensorrt_llm \
-nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc3 \
+nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc4 \
/bin/bash
@@ -1086,9 +1086,9 @@ chmod +x bench.sh
diff --git a/deployment-guide/deployment-guide-for-qwen3-next-on-trtllm.html b/deployment-guide/deployment-guide-for-qwen3-next-on-trtllm.html
index d3d78ea757..fdcf4af7bd 100644
--- a/deployment-guide/deployment-guide-for-qwen3-next-on-trtllm.html
+++ b/deployment-guide/deployment-guide-for-qwen3-next-on-trtllm.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -929,9 +929,9 @@ chmod +x bench.sh
diff --git a/deployment-guide/index.html b/deployment-guide/index.html
index 67eb76028a..15f9dadacc 100644
--- a/deployment-guide/index.html
+++ b/deployment-guide/index.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -766,9 +766,9 @@
diff --git a/developer-guide/api-change.html b/developer-guide/api-change.html
index 7de118c98a..832fb21374 100644
--- a/developer-guide/api-change.html
+++ b/developer-guide/api-change.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -1034,9 +1034,9 @@ python -m pytest <
diff --git a/developer-guide/ci-overview.html b/developer-guide/ci-overview.html
index 31315e11c9..ebedfac175 100644
--- a/developer-guide/ci-overview.html
+++ b/developer-guide/ci-overview.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -790,9 +790,9 @@ selective keeps CI turnaround fast and conserves hardware resources.
diff --git a/developer-guide/dev-containers.html b/developer-guide/dev-containers.html
index ac50b8b96a..6362063065 100644
--- a/developer-guide/dev-containers.html
+++ b/developer-guide/dev-containers.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -752,9 +752,9 @@ initialization script will create one with the contents listed above.
diff --git a/developer-guide/kv-transfer.html b/developer-guide/kv-transfer.html
index 9b30101cce..86668e3cd0 100644
--- a/developer-guide/kv-transfer.html
+++ b/developer-guide/kv-transfer.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -750,9 +750,9 @@
diff --git a/developer-guide/overview.html b/developer-guide/overview.html
index d8f93dd695..7049ccada2 100644
--- a/developer-guide/overview.html
+++ b/developer-guide/overview.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -718,9 +718,9 @@
diff --git a/developer-guide/perf-analysis.html b/developer-guide/perf-analysis.html
index 5447b6c1e4..46aae45e9a 100644
--- a/developer-guide/perf-analysis.html
+++ b/developer-guide/perf-analysis.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -765,9 +765,9 @@ python3 benchmarks/cpp/prepare_dataset.py
diff --git a/developer-guide/perf-benchmarking.html b/developer-guide/perf-benchmarking.html
index 3f9ade7bfa..6f45bf4d90 100644
--- a/developer-guide/perf-benchmarking.html
+++ b/developer-guide/perf-benchmarking.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -1170,9 +1170,9 @@ when the checkpoint precision is
- Last updated on November 20, 2025.
+ Last updated on November 23, 2025.
- This page is generated by TensorRT-LLM commit 2128f73.
+ This page is generated by TensorRT-LLM commit a761585.
diff --git a/developer-guide/perf-overview.html b/developer-guide/perf-overview.html
index a65e07b878..cac5f4af89 100644
--- a/developer-guide/perf-overview.html
+++ b/developer-guide/perf-overview.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -1360,7 +1360,7 @@ nvidia/Qwen3-235B-A22B-FP8
Preparing a Dataset#
-In order to prepare a dataset, you can use the provided script.
+
In order to prepare a dataset, you can use the provided script.
To generate a synthetic dataset, run the following command:
python benchmarks/cpp/prepare_dataset.py --tokenizer=$model_name --stdout token-norm-dist --num-requests=$num_requests --input-mean=$isl --output-mean=$osl --input-stdev=0 --output-stdev=0 > $dataset_file
@@ -1440,7 +1440,7 @@ remain in the system longer and therefore require less requests to achieve stead
Running the Benchmark#
To run the benchmark with the generated data set, simply use the trtllm-bench throughput subcommand. The benchmarker will
run an offline maximum throughput scenario such that all requests are queued in rapid succession. You simply need to provide
-a model name (HuggingFace reference or path to a local model), a generated dataset, and a file containing any desired extra options to the LLM APIs (details in tensorrt_llm/llmapi/llm_args.py:LlmArgs).
+a model name (HuggingFace reference or path to a local model), a generated dataset, and a file containing any desired extra options to the LLM APIs (details in tensorrt_llm/llmapi/llm_args.py:LlmArgs).
For dense / non-MoE models:
trtllm-bench --tp $tp_size --pp $pp_size --model $model_name throughput --dataset $dataset_file --backend pytorch --extra_llm_api_options $llm_options
@@ -1693,9 +1693,9 @@ using the --kv_cach
diff --git a/examples/curl_chat_client.html b/examples/curl_chat_client.html
index ef1f3ea393..82b4c75251 100644
--- a/examples/curl_chat_client.html
+++ b/examples/curl_chat_client.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -516,7 +516,7 @@
Curl Chat Client#
Refer to the trtllm-serve documentation for starting a server.
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1#! /usr/bin/env bash
2
3curl http://localhost:8000/v1/chat/completions \
@@ -657,9 +657,9 @@
diff --git a/examples/curl_chat_client_for_multimodal.html b/examples/curl_chat_client_for_multimodal.html
index 76a86c268c..dec55b44ad 100644
--- a/examples/curl_chat_client_for_multimodal.html
+++ b/examples/curl_chat_client_for_multimodal.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -516,7 +516,7 @@
Curl Chat Client For Multimodal#
Refer to the trtllm-serve documentation for starting a server.
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1#! /usr/bin/env bash
2
3# SINGLE IMAGE INFERENCE
@@ -734,9 +734,9 @@
diff --git a/examples/curl_completion_client.html b/examples/curl_completion_client.html
index 3f6a5c50a9..4cd167f062 100644
--- a/examples/curl_completion_client.html
+++ b/examples/curl_completion_client.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -516,7 +516,7 @@
Curl Completion Client#
Refer to the trtllm-serve documentation for starting a server.
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1#! /usr/bin/env bash
2
3curl http://localhost:8000/v1/completions \
@@ -656,9 +656,9 @@
diff --git a/examples/customization.html b/examples/customization.html
index 162d0ed41e..3ba5078ba3 100644
--- a/examples/customization.html
+++ b/examples/customization.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -773,9 +773,9 @@
diff --git a/examples/deepseek_r1_reasoning_parser.html b/examples/deepseek_r1_reasoning_parser.html
index 166c34a10f..b986a6ced9 100644
--- a/examples/deepseek_r1_reasoning_parser.html
+++ b/examples/deepseek_r1_reasoning_parser.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -516,7 +516,7 @@
Deepseek R1 Reasoning Parser#
Refer to the trtllm-serve documentation for starting a server.
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1#! /usr/bin/env bash
2
3trtllm-serve \
@@ -656,9 +656,9 @@
diff --git a/examples/dynamo_k8s_example.html b/examples/dynamo_k8s_example.html
index e6eb6a5862..8ab3a73dcf 100644
--- a/examples/dynamo_k8s_example.html
+++ b/examples/dynamo_k8s_example.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -653,9 +653,9 @@ for more details.
diff --git a/examples/genai_perf_client.html b/examples/genai_perf_client.html
index 8b32681ce0..b102aa629f 100644
--- a/examples/genai_perf_client.html
+++ b/examples/genai_perf_client.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -516,7 +516,7 @@
Genai Perf Client#
Refer to the trtllm-serve documentation for starting a server.
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1#! /usr/bin/env bash
2
3genai-perf profile \
@@ -662,9 +662,9 @@
diff --git a/examples/genai_perf_client_for_multimodal.html b/examples/genai_perf_client_for_multimodal.html
index 727eaf5636..94627384cc 100644
--- a/examples/genai_perf_client_for_multimodal.html
+++ b/examples/genai_perf_client_for_multimodal.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -516,7 +516,7 @@
Genai Perf Client For Multimodal#
Refer to the trtllm-serve documentation for starting a server.
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1#! /usr/bin/env bash
2
3genai-perf profile \
@@ -665,9 +665,9 @@
diff --git a/examples/index.html b/examples/index.html
index 17b2c3ed1e..1799d82956 100644
--- a/examples/index.html
+++ b/examples/index.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -663,9 +663,9 @@
diff --git a/examples/kvcacheconfig.html b/examples/kvcacheconfig.html
index 284bdc450b..4f8f0b9e10 100644
--- a/examples/kvcacheconfig.html
+++ b/examples/kvcacheconfig.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -658,9 +658,9 @@
diff --git a/examples/kvcacheretentionconfig.html b/examples/kvcacheretentionconfig.html
index 006422be18..48f7efad23 100644
--- a/examples/kvcacheretentionconfig.html
+++ b/examples/kvcacheretentionconfig.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -681,9 +681,9 @@
diff --git a/examples/llm_api_examples.html b/examples/llm_api_examples.html
index 7660b640ea..62fc99ca16 100644
--- a/examples/llm_api_examples.html
+++ b/examples/llm_api_examples.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -698,9 +698,9 @@
diff --git a/examples/llm_guided_decoding.html b/examples/llm_guided_decoding.html
index 76de28edb5..08be3da6c3 100644
--- a/examples/llm_guided_decoding.html
+++ b/examples/llm_guided_decoding.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Generate text with guided decoding#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1from tensorrt_llm import LLM, SamplingParams
2from tensorrt_llm.llmapi import GuidedDecodingParams
3
@@ -689,9 +689,9 @@
diff --git a/examples/llm_inference.html b/examples/llm_inference.html
index c5bd05680a..d7154d0e17 100644
--- a/examples/llm_inference.html
+++ b/examples/llm_inference.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Generate text#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1from tensorrt_llm import LLM, SamplingParams
2
3
@@ -677,9 +677,9 @@
diff --git a/examples/llm_inference_async.html b/examples/llm_inference_async.html
index bef53a3e91..245c352816 100644
--- a/examples/llm_inference_async.html
+++ b/examples/llm_inference_async.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Generate text asynchronously#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1import asyncio
2
3from tensorrt_llm import LLM, SamplingParams
@@ -685,9 +685,9 @@
diff --git a/examples/llm_inference_async_streaming.html b/examples/llm_inference_async_streaming.html
index c9ce26a8c3..7b8d10a20d 100644
--- a/examples/llm_inference_async_streaming.html
+++ b/examples/llm_inference_async_streaming.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Generate text in streaming#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1import asyncio
2
3from tensorrt_llm import LLM, SamplingParams
@@ -706,9 +706,9 @@
diff --git a/examples/llm_inference_distributed.html b/examples/llm_inference_distributed.html
index 3af9b4b703..afbf1942bb 100644
--- a/examples/llm_inference_distributed.html
+++ b/examples/llm_inference_distributed.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Distributed LLM Generation#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1from tensorrt_llm import LLM, SamplingParams
2
3
@@ -686,9 +686,9 @@
diff --git a/examples/llm_kv_cache_connector.html b/examples/llm_kv_cache_connector.html
index 324afda46c..10c25fc75c 100644
--- a/examples/llm_kv_cache_connector.html
+++ b/examples/llm_kv_cache_connector.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
KV Cache Connector#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1
2import os
3import sys
@@ -889,9 +889,9 @@
diff --git a/examples/llm_kv_cache_offloading.html b/examples/llm_kv_cache_offloading.html
index f4c4fe07bd..cca0ae57b0 100644
--- a/examples/llm_kv_cache_offloading.html
+++ b/examples/llm_kv_cache_offloading.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
KV Cache Offloading#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1'''
2This script demonstrates the effectiveness of KV cache host offloading in TensorRT-LLM.
3
@@ -776,9 +776,9 @@
diff --git a/examples/llm_logits_processor.html b/examples/llm_logits_processor.html
index 0b14913d01..710fb79ab4 100644
--- a/examples/llm_logits_processor.html
+++ b/examples/llm_logits_processor.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Control generated text using logits processor#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1from typing import List, Optional
2
3import torch
@@ -770,9 +770,9 @@
diff --git a/examples/llm_mgmn_llm_distributed.html b/examples/llm_mgmn_llm_distributed.html
index 0cfd12b2a1..3cd5f1c981 100644
--- a/examples/llm_mgmn_llm_distributed.html
+++ b/examples/llm_mgmn_llm_distributed.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Run LLM-API with pytorch backend on Slurm#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1#!/bin/bash
2#SBATCH -A <account> # parameter
3#SBATCH -p <partition> # parameter
@@ -697,9 +697,9 @@
diff --git a/examples/llm_mgmn_trtllm_bench.html b/examples/llm_mgmn_trtllm_bench.html
index b9fb318c97..d91523325d 100644
--- a/examples/llm_mgmn_trtllm_bench.html
+++ b/examples/llm_mgmn_trtllm_bench.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Run trtllm-bench with pytorch backend on Slurm#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1#!/bin/bash
2#SBATCH -A <account>
3#SBATCH -p <partition>
@@ -737,9 +737,9 @@
diff --git a/examples/llm_mgmn_trtllm_serve.html b/examples/llm_mgmn_trtllm_serve.html
index 04cdb337cd..e8fee8c0f7 100644
--- a/examples/llm_mgmn_trtllm_serve.html
+++ b/examples/llm_mgmn_trtllm_serve.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Run trtllm-serve with pytorch backend on Slurm#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1#!/bin/bash
2#SBATCH -A <account>
3#SBATCH -p <partition>
@@ -698,9 +698,9 @@
diff --git a/examples/llm_multilora.html b/examples/llm_multilora.html
index b0962efb50..f51039eec6 100644
--- a/examples/llm_multilora.html
+++ b/examples/llm_multilora.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Generate text with multiple LoRA adapters#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1
2import argparse
3from typing import Optional
@@ -731,9 +731,9 @@
diff --git a/examples/llm_runtime.html b/examples/llm_runtime.html
index ca1e9d2eec..53c09e7f7e 100644
--- a/examples/llm_runtime.html
+++ b/examples/llm_runtime.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Runtime Configuration Examples#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1
2import argparse
3
@@ -738,9 +738,9 @@
diff --git a/examples/llm_sampling.html b/examples/llm_sampling.html
index 2e81e93761..bdc8116c64 100644
--- a/examples/llm_sampling.html
+++ b/examples/llm_sampling.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Sampling Techniques Showcase#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1"""
2This example demonstrates various sampling techniques available in TensorRT-LLM.
3It showcases different sampling parameters and their effects on text generation.
@@ -871,9 +871,9 @@
diff --git a/examples/llm_sparse_attention.html b/examples/llm_sparse_attention.html
index 3c4fa2803c..a32eb5c8e2 100644
--- a/examples/llm_sparse_attention.html
+++ b/examples/llm_sparse_attention.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Sparse Attention#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1"""
2This example demonstrates how to use sparse attention with TensorRT-LLM.
3
@@ -851,9 +851,9 @@
diff --git a/examples/llm_speculative_decoding.html b/examples/llm_speculative_decoding.html
index fc712b8eaa..cd3453b432 100644
--- a/examples/llm_speculative_decoding.html
+++ b/examples/llm_speculative_decoding.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -515,7 +515,7 @@
Speculative Decoding#
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1from typing import Optional
2
3import click
@@ -737,9 +737,9 @@
diff --git a/examples/openai_chat_client.html b/examples/openai_chat_client.html
index 86fe4780fb..02762c1386 100644
--- a/examples/openai_chat_client.html
+++ b/examples/openai_chat_client.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -516,7 +516,7 @@
OpenAI Chat Client#
Refer to the trtllm-serve documentation for starting a server.
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1
2from openai import OpenAI
3
@@ -666,9 +666,9 @@
diff --git a/examples/openai_chat_client_for_multimodal.html b/examples/openai_chat_client_for_multimodal.html
index f455441ee7..cf0bfcad45 100644
--- a/examples/openai_chat_client_for_multimodal.html
+++ b/examples/openai_chat_client_for_multimodal.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -516,7 +516,7 @@
OpenAI Chat Client for Multimodal#
Refer to the trtllm-serve documentation for starting a server.
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1
2import os
3from pathlib import Path
@@ -774,9 +774,9 @@
diff --git a/examples/openai_completion_client.html b/examples/openai_completion_client.html
index 0e5b0872df..6da771e77f 100644
--- a/examples/openai_completion_client.html
+++ b/examples/openai_completion_client.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -516,7 +516,7 @@
OpenAI Completion Client#
Refer to the trtllm-serve documentation for starting a server.
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1
2from openai import OpenAI
3
@@ -660,9 +660,9 @@
diff --git a/examples/openai_completion_client_for_lora.html b/examples/openai_completion_client_for_lora.html
index 7b48cd9636..42044db6c8 100644
--- a/examples/openai_completion_client_for_lora.html
+++ b/examples/openai_completion_client_for_lora.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -516,7 +516,7 @@
Openai Completion Client For Lora#
Refer to the trtllm-serve documentation for starting a server.
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1### OpenAI Completion Client
2
3import os
@@ -676,9 +676,9 @@
diff --git a/examples/openai_completion_client_json_schema.html b/examples/openai_completion_client_json_schema.html
index e32b959391..48ba2499a7 100644
--- a/examples/openai_completion_client_json_schema.html
+++ b/examples/openai_completion_client_json_schema.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -516,7 +516,7 @@
OpenAI Completion Client with JSON Schema#
Refer to the trtllm-serve documentation for starting a server.
-Source NVIDIA/TensorRT-LLM.
+Source NVIDIA/TensorRT-LLM.
1
2# This example requires to specify `guided_decoding_backend` as
3# `xgrammar` or `llguidance` in the extra_llm_api_options.yaml file.
@@ -697,9 +697,9 @@
diff --git a/examples/trtllm_serve_examples.html b/examples/trtllm_serve_examples.html
index 040cf6df52..16c6157332 100644
--- a/examples/trtllm_serve_examples.html
+++ b/examples/trtllm_serve_examples.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -654,9 +654,9 @@
diff --git a/features/additional-outputs.html b/features/additional-outputs.html
index 9d1e2e4d26..2619b388bd 100644
--- a/features/additional-outputs.html
+++ b/features/additional-outputs.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -724,9 +724,9 @@ and sequence.additi
diff --git a/features/attention.html b/features/attention.html
index 5a50ed43c7..111ab5c4af 100644
--- a/features/attention.html
+++ b/features/attention.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -852,7 +852,7 @@ reach that point).
the different requests by a cache manager during processing. That cache manager
keeps track of the sequences, allocates new blocks from a pool and recycles those
blocks when required. See the implementation of
-KVCacheManager.
+KVCacheManager.
INT8/FP8 KV Caches#
@@ -1143,9 +1143,9 @@ is computed as:
diff --git a/features/auto_deploy/advanced/benchmarking_with_trtllm_bench.html b/features/auto_deploy/advanced/benchmarking_with_trtllm_bench.html
index 59f84ceaef..298962d8af 100644
--- a/features/auto_deploy/advanced/benchmarking_with_trtllm_bench.html
+++ b/features/auto_deploy/advanced/benchmarking_with_trtllm_bench.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -780,9 +780,9 @@
diff --git a/features/auto_deploy/advanced/example_run.html b/features/auto_deploy/advanced/example_run.html
index 8567d5503e..41bc68ac07 100644
--- a/features/auto_deploy/advanced/example_run.html
+++ b/features/auto_deploy/advanced/example_run.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -696,9 +696,9 @@ python build_and_run_ad.py
diff --git a/features/auto_deploy/advanced/expert_configurations.html b/features/auto_deploy/advanced/expert_configurations.html
index 0b9aa3d6d1..e8d6a06ec5 100644
--- a/features/auto_deploy/advanced/expert_configurations.html
+++ b/features/auto_deploy/advanced/expert_configurations.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -803,9 +803,9 @@ python build_and_run_ad.py
diff --git a/features/auto_deploy/advanced/logging.html b/features/auto_deploy/advanced/logging.html
index a3858d8323..972033d01a 100644
--- a/features/auto_deploy/advanced/logging.html
+++ b/features/auto_deploy/advanced/logging.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -629,9 +629,9 @@ decreasing verbosity;
diff --git a/features/auto_deploy/advanced/workflow.html b/features/auto_deploy/advanced/workflow.html
index 25e0b98dac..684882007f 100644
--- a/features/auto_deploy/advanced/workflow.html
+++ b/features/auto_deploy/advanced/workflow.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -642,9 +642,9 @@
diff --git a/features/auto_deploy/auto-deploy.html b/features/auto_deploy/auto-deploy.html
index 18f1daa776..8c3fa09de3 100644
--- a/features/auto_deploy/auto-deploy.html
+++ b/features/auto_deploy/auto-deploy.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -739,9 +739,9 @@ We welcome community contributions, see
diff --git a/features/auto_deploy/support_matrix.html b/features/auto_deploy/support_matrix.html
index 6156140473..b4048fa3b1 100644
--- a/features/auto_deploy/support_matrix.html
+++ b/features/auto_deploy/support_matrix.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -805,9 +805,9 @@ In addition, the following models have been officially validated using the defau
diff --git a/features/checkpoint-loading.html b/features/checkpoint-loading.html
index 4596d00396..d6a0358b1f 100644
--- a/features/checkpoint-loading.html
+++ b/features/checkpoint-loading.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -1001,9 +1001,9 @@ Likewise, if the format shares some components with an already supported framewo
diff --git a/features/disagg-serving.html b/features/disagg-serving.html
index 62550c4bff..f160aca72c 100644
--- a/features/disagg-serving.html
+++ b/features/disagg-serving.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -901,9 +901,9 @@ when routing requests to the generation servers, the disaggregated server will m
diff --git a/features/feature-combination-matrix.html b/features/feature-combination-matrix.html
index 5d9b5cee89..17dde78cd6 100644
--- a/features/feature-combination-matrix.html
+++ b/features/feature-combination-matrix.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -918,9 +918,9 @@
diff --git a/features/kvcache.html b/features/kvcache.html
index 4ba059e3a2..f338b1224b 100644
--- a/features/kvcache.html
+++ b/features/kvcache.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -750,9 +750,9 @@
diff --git a/features/long-sequence.html b/features/long-sequence.html
index 6d09ff062f..560ffdc196 100644
--- a/features/long-sequence.html
+++ b/features/long-sequence.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -719,9 +719,9 @@
diff --git a/features/lora.html b/features/lora.html
index c9951e1757..e899984913 100644
--- a/features/lora.html
+++ b/features/lora.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -923,9 +923,9 @@
diff --git a/features/multi-modality.html b/features/multi-modality.html
index 5672c457fe..b12177cff4 100644
--- a/features/multi-modality.html
+++ b/features/multi-modality.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -546,7 +546,7 @@
The following examples demonstrate how to use TensorRT LLM’s multimodal support in various scenarios, including quick run examples, serving endpoints, and performance benchmarking.
Quick start#
-Quickly try out TensorRT LLM’s multimodal support using our LLM-API and a ready-to-run example:
+Quickly try out TensorRT LLM’s multimodal support using our LLM-API and a ready-to-run example:
python3 quickstart_multimodal.py --model_dir Efficient-Large-Model/NVILA-8B --modality image --disable_kv_cache_reuse
@@ -557,7 +557,7 @@
trtllm-serve Qwen/Qwen2-VL-7B-Instruct --backend pytorch
-You can then send OpenAI-compatible requests, such as via curl or API clients, to the server endpoint. See curl chat client for multimodal script as an example.
+You can then send OpenAI-compatible requests, such as via curl or API clients, to the server endpoint. See curl chat client for multimodal script as an example.
Run with trtllm-bench#
@@ -715,9 +715,9 @@
diff --git a/features/overlap-scheduler.html b/features/overlap-scheduler.html
index 5462b96eec..a81478d68e 100644
--- a/features/overlap-scheduler.html
+++ b/features/overlap-scheduler.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -697,9 +697,9 @@
diff --git a/features/paged-attention-ifb-scheduler.html b/features/paged-attention-ifb-scheduler.html
index f57cd9aff5..77f7cd1a47 100644
--- a/features/paged-attention-ifb-scheduler.html
+++ b/features/paged-attention-ifb-scheduler.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -602,9 +602,9 @@ different types of KV caches: contiguous and pagedThe paged KV cache decomposes the KV cache into blocks that are distributed to
the different requests by a cache manager during processing. That cache manager
keeps track of the sequences, allocates new blocks from a pool, and recycles those blocks when required. See the simplified implementation of
-tensorrt_llm.runtime.KVCacheManager.
+tensorrt_llm.runtime.KVCacheManager.
A more efficient C++ implementation is included in the
-Batch Manager.
+Batch Manager.
@@ -793,9 +793,9 @@ A more efficient C++ implementation is included in the
diff --git a/features/parallel-strategy.html b/features/parallel-strategy.html
index a720a741dc..51089555e1 100644
--- a/features/parallel-strategy.html
+++ b/features/parallel-strategy.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -902,9 +902,9 @@
diff --git a/features/quantization.html b/features/quantization.html
index 2363663cbc..3aba47f4f5 100644
--- a/features/quantization.html
+++ b/features/quantization.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -1084,9 +1084,9 @@ The language component decides which quantization methods are supported by a giv
diff --git a/features/ray-orchestrator.html b/features/ray-orchestrator.html
index d68e75b024..8caf571aec 100644
--- a/features/ray-orchestrator.html
+++ b/features/ray-orchestrator.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -706,9 +706,9 @@ pip install -r
diff --git a/features/sampling.html b/features/sampling.html
index 6e611c8c0d..f3cb56be64 100644
--- a/features/sampling.html
+++ b/features/sampling.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -522,7 +522,7 @@
To use the feature:
Enable the enable_trtllm_sampler option in the LLM class
-Pass a SamplingParams object with the desired options to the generate() function
+Pass a SamplingParams object with the desired options to the generate() function
The following example prepares two identical prompts which will give different results due to the sampling parameters chosen:
from tensorrt_llm import LLM, SamplingParams
@@ -587,7 +587,7 @@
To enable guided decoding, you must:
Set the guided_decoding_backend parameter to 'xgrammar' or 'llguidance' in the LLM class
-Create a GuidedDecodingParams object with the desired format specification
+Create a GuidedDecodingParams object with the desired format specification
Note: Depending on the type of format, a different parameter needs to be chosen to construct the object (json, regex, grammar, structural_tag).
@@ -608,14 +608,14 @@
llm.generate("Generate a JSON response", sampling_params)
-You can find a more detailed example on guided decoding here.
+You can find a more detailed example on guided decoding here.
Logits processor#
Logits processors allow you to modify the logits produced by the network before sampling, enabling custom generation behavior and constraints.
To use a custom logits processor:
-Create a custom class that inherits from LogitsProcessor and implements the __call__ method
+Create a custom class that inherits from LogitsProcessor and implements the __call__ method
Pass an instance of this class to the logits_processor parameter of SamplingParams
The following example demonstrates logits processing:
@@ -643,7 +643,7 @@
llm.generate(["Hello, my name is"], sampling_params)
-You can find a more detailed example on logits processors here.
+You can find a more detailed example on logits processors here.
@@ -791,9 +791,9 @@
diff --git a/features/speculative-decoding.html b/features/speculative-decoding.html
index 23c53497cd..761b920538 100644
--- a/features/speculative-decoding.html
+++ b/features/speculative-decoding.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -938,9 +938,9 @@ function. In practice, this is very cheap since the blocks are just marked as av
diff --git a/features/torch_compile_and_piecewise_cuda_graph.html b/features/torch_compile_and_piecewise_cuda_graph.html
index 2d2bb8f916..1cb02835b2 100644
--- a/features/torch_compile_and_piecewise_cuda_graph.html
+++ b/features/torch_compile_and_piecewise_cuda_graph.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -1079,9 +1079,9 @@
diff --git a/genindex.html b/genindex.html
index dc45b79d85..f895366109 100644
--- a/genindex.html
+++ b/genindex.html
@@ -60,7 +60,7 @@
@@ -73,7 +73,7 @@
-
+
@@ -630,6 +630,8 @@
@@ -969,6 +971,8 @@
trtllm-eval-mmmu command line option
+
+
-
--max_seq_len
@@ -984,8 +988,6 @@
- trtllm-serve-serve command line option
-
-
-
--media_io_kwargs
@@ -13173,6 +13175,8 @@
- --backend
- --cluster_size
+
+ - --custom_module_dirs
- --disagg_cluster_uri
@@ -13844,9 +13848,9 @@
diff --git a/index.html b/index.html
index 7a1e988852..3189a5abe6 100644
--- a/index.html
+++ b/index.html
@@ -63,7 +63,7 @@
@@ -77,7 +77,7 @@
-
+
@@ -1150,9 +1150,9 @@
diff --git a/installation/build-from-source-linux.html b/installation/build-from-source-linux.html
index b41ec8f2de..ae3764120d 100644
--- a/installation/build-from-source-linux.html
+++ b/installation/build-from-source-linux.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -674,7 +674,7 @@ example:
python3 ./scripts/build_wheel.py --cuda_architectures "80-real;86-real"
-To use the C++ benchmark scripts under benchmark/cpp, for example gptManagerBenchmark.cpp, add the --benchmarks option:
+To use the C++ benchmark scripts under benchmark/cpp, for example gptManagerBenchmark.cpp, add the --benchmarks option:
python3 ./scripts/build_wheel.py --benchmarks
@@ -898,9 +898,9 @@ pip install ./build/tensorrt_llm*.
diff --git a/installation/containers.html b/installation/containers.html
index 2fe9f2e791..ec42520286 100644
--- a/installation/containers.html
+++ b/installation/containers.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -521,7 +521,7 @@ on NGC. This is likely the simplest way to obtain TensorRT LLM. Please refer to
Container image tags
In the example shell commands, x.y.z corresponds to the TensorRT-LLM container
version to use. If omitted, IMAGE_TAG will default to tensorrt_llm.__version__
-(e.g., this documentation was generated from the 1.2.0rc3 source tree).
+(e.g., this documentation was generated from the 1.2.0rc4 source tree).
If this does not work, e.g., because a container for the version you are
currently working with has not been released yet, you can try using a
container published for a previous
@@ -658,9 +658,9 @@ for all related options.
diff --git a/installation/index.html b/installation/index.html
index 6aaaa87493..4e55eeb476 100644
--- a/installation/index.html
+++ b/installation/index.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -648,9 +648,9 @@
diff --git a/installation/linux.html b/installation/linux.html
index 78374e90ea..37c8ac3441 100644
--- a/installation/linux.html
+++ b/installation/linux.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -733,9 +733,9 @@ pip3 install --upgrade
- Last updated on November 20, 2025.
+ Last updated on November 23, 2025.
- This page is generated by TensorRT-LLM commit 2128f73.
+ This page is generated by TensorRT-LLM commit a761585.
diff --git a/legacy/advanced/disaggregated-service.html b/legacy/advanced/disaggregated-service.html
index d21560fd48..c8058ed411 100644
--- a/legacy/advanced/disaggregated-service.html
+++ b/legacy/advanced/disaggregated-service.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -702,9 +702,9 @@ This feature is currently in prototype, and the related API is subjected to chan
diff --git a/legacy/advanced/executor.html b/legacy/advanced/executor.html
index 2954a087a5..ae12628df8 100644
--- a/legacy/advanced/executor.html
+++ b/legacy/advanced/executor.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -517,7 +517,7 @@
TensorRT-LLM includes a high-level C++ API called the Executor API which allows you to execute requests
asynchronously, with in-flight batching, and without the need to define callbacks.
A software component (referred to as “the client” in the text that follows) can interact
-with the executor using the API defined in the executor.h file.
+with the executor using the API defined in the executor.h file.
For details about the API, refer to the _cpp_gen/executor.rst.
The following sections provide an overview of the main classes defined in the Executor API.
@@ -585,7 +585,7 @@ This allows the runtime to reconfigure itself for a new beam width when no reque
stop_token_ids = [tokenizer.eos_token_id]
-Refer to tensorrt_llm/llmapi/tokenizer.py for more details. You may dump these materials to disk, and reload them to C++ runtime for use.
+Refer to tensorrt_llm/llmapi/tokenizer.py for more details. You may dump these materials to disk, and reload them to C++ runtime for use.
Each request can be optionally specified with a GuidedDecodingParams, which defines the desired structured format. Currently, it supports four types:
GuidedDecodingParams::GuideType::kJSON: The generated text is amenable to JSON format;
@@ -634,12 +634,12 @@ This allows the runtime to reconfigure itself for a new beam width when no reque
C++ Executor API Example#
-Two C++ examples are provided that shows how to use the Executor API and can be found in the examples/cpp/executor folder.
+Two C++ examples are provided that shows how to use the Executor API and can be found in the examples/cpp/executor folder.
Python Bindings for the Executor API#
-Python bindings for the Executor API are also available to use the Executor API from Python. The Python bindings are defined in bindings.cpp and once built, are available in package tensorrt_llm.bindings.executor. Running 'help('tensorrt_llm.bindings.executor') in a Python interpreter will provide an overview of the classes available.
-In addition, three Python examples are provided to demonstrate how to use the Python bindings to the Executor API for single and multi-GPU models. They can be found in examples/bindings.
+Python bindings for the Executor API are also available to use the Executor API from Python. The Python bindings are defined in bindings.cpp and once built, are available in package tensorrt_llm.bindings.executor. Running 'help('tensorrt_llm.bindings.executor') in a Python interpreter will provide an overview of the classes available.
+In addition, three Python examples are provided to demonstrate how to use the Python bindings to the Executor API for single and multi-GPU models. They can be found in examples/bindings.
In-flight Batching with the Triton Inference Server#
@@ -794,9 +794,9 @@ the TensorRT-LLM C++ Executor API.
diff --git a/legacy/advanced/expert-parallelism.html b/legacy/advanced/expert-parallelism.html
index 333005db8c..b5cfdb490a 100644
--- a/legacy/advanced/expert-parallelism.html
+++ b/legacy/advanced/expert-parallelism.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -660,9 +660,9 @@
diff --git a/legacy/advanced/gpt-attention.html b/legacy/advanced/gpt-attention.html
index 1897dbad1b..06e2527fcd 100644
--- a/legacy/advanced/gpt-attention.html
+++ b/legacy/advanced/gpt-attention.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -685,9 +685,9 @@ reach that point).
the different requests by a cache manager during processing. That cache manager
keeps track of the sequences, allocate new blocks from a pool and recycle those
blocks when required. See the simplified implementation of
-tensorrt_llm.runtime.KVCacheManager.
+tensorrt_llm.runtime.KVCacheManager.
A more efficient C++ implementation is included in the
-Batch Manager.
+Batch Manager.
@@ -977,9 +977,9 @@ is computed as:
diff --git a/legacy/advanced/gpt-runtime.html b/legacy/advanced/gpt-runtime.html
index 68b1a23f2b..953cf6d029 100644
--- a/legacy/advanced/gpt-runtime.html
+++ b/legacy/advanced/gpt-runtime.html
@@ -63,7 +63,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -1022,9 +1022,9 @@ The GptDecoder
- Last updated on November 20, 2025.
+ Last updated on November 23, 2025.
- This page is generated by TensorRT-LLM commit 2128f73.
+ This page is generated by TensorRT-LLM commit a761585.
diff --git a/legacy/advanced/graph-rewriting.html b/legacy/advanced/graph-rewriting.html
index 3bec264a88..9a9431809d 100644
--- a/legacy/advanced/graph-rewriting.html
+++ b/legacy/advanced/graph-rewriting.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -840,9 +840,9 @@ techniques to optimize the underlying graph. It provides a wrapper similar to P
diff --git a/legacy/advanced/kv-cache-management.html b/legacy/advanced/kv-cache-management.html
index 17dc56486a..2c32ec5b67 100644
--- a/legacy/advanced/kv-cache-management.html
+++ b/legacy/advanced/kv-cache-management.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -745,9 +745,9 @@ An “event” is any significant change in the lifecycle or state of a KV cache
diff --git a/legacy/advanced/kv-cache-reuse.html b/legacy/advanced/kv-cache-reuse.html
index 0ded2e3d5b..ca3f9eae58 100644
--- a/legacy/advanced/kv-cache-reuse.html
+++ b/legacy/advanced/kv-cache-reuse.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -718,9 +718,9 @@ Assume vocabulary size is 100, which means normal text token ids are in range [0
diff --git a/legacy/advanced/lora.html b/legacy/advanced/lora.html
index 74c2c775e9..8d819bbe78 100644
--- a/legacy/advanced/lora.html
+++ b/legacy/advanced/lora.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -832,9 +832,9 @@ The shape of LoraWe
diff --git a/legacy/advanced/lowprecision-pcie-allreduce.html b/legacy/advanced/lowprecision-pcie-allreduce.html
index 903e68306c..a20644cced 100644
--- a/legacy/advanced/lowprecision-pcie-allreduce.html
+++ b/legacy/advanced/lowprecision-pcie-allreduce.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -701,9 +701,9 @@ This feature is optimized for PCIe-based GPU topologies and may affect model acc
diff --git a/legacy/advanced/open-sourced-cutlass-kernels.html b/legacy/advanced/open-sourced-cutlass-kernels.html
index a1cecba6b3..7998ec3584 100644
--- a/legacy/advanced/open-sourced-cutlass-kernels.html
+++ b/legacy/advanced/open-sourced-cutlass-kernels.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -656,9 +656,9 @@ Note that support for these static libraries will be gradually deprioritized in
diff --git a/legacy/advanced/speculative-decoding.html b/legacy/advanced/speculative-decoding.html
index 7f49445b31..a9c584c2b4 100644
--- a/legacy/advanced/speculative-decoding.html
+++ b/legacy/advanced/speculative-decoding.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -832,9 +832,9 @@ However, similar to any new model, you can follow the same approach to define yo
diff --git a/legacy/advanced/weight-streaming.html b/legacy/advanced/weight-streaming.html
index 690e32681b..3d52504b14 100644
--- a/legacy/advanced/weight-streaming.html
+++ b/legacy/advanced/weight-streaming.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -689,9 +689,9 @@ python3 examples/summarize.py
- Last updated on November 20, 2025.
+ Last updated on November 23, 2025.
- This page is generated by TensorRT-LLM commit 2128f73.
+ This page is generated by TensorRT-LLM commit a761585.
diff --git a/legacy/architecture/add-model.html b/legacy/architecture/add-model.html
index b8e98b4650..911cfa7de6 100644
--- a/legacy/architecture/add-model.html
+++ b/legacy/architecture/add-model.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -731,9 +731,9 @@ python ../summarize.py --engine_di
diff --git a/legacy/architecture/checkpoint.html b/legacy/architecture/checkpoint.html
index 67fb58c8f3..2b332fd142 100644
--- a/legacy/architecture/checkpoint.html
+++ b/legacy/architecture/checkpoint.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -998,9 +998,9 @@ trtllm-build --checkpoint_dir ./op
diff --git a/legacy/architecture/core-concepts.html b/legacy/architecture/core-concepts.html
index 174bcc7910..fe74a16a78 100644
--- a/legacy/architecture/core-concepts.html
+++ b/legacy/architecture/core-concepts.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -521,7 +521,7 @@ to create graph representations of deep neural networks in TensorRT. To become
familiar with the core concepts of the TensorRT API, refer to the
Core Concepts
section of the TensorRT documentation before proceeding further.
-In TensorRT-LLM, the tensorrt_llm.Builder class
+
In TensorRT-LLM, the tensorrt_llm.Builder class
contains a
tensorrt.Builder
object. That instance is used in the tensorrt_llm.Builder.create_network
@@ -529,7 +529,7 @@ method to create an instance of the
tensorrt.INetworkDefinition
class. The INetworkDefinition object can then be populated using the free
functions defined in the
-tensorrt_llm.functional.
+tensorrt_llm.functional.
A simple example of such a free function is tensorrt_llm.activation that inserts a
tensorrt.IActivationLayer
node in the graph of the model:
@@ -664,14 +664,14 @@ limitation, TensorRT offers a powerful mechanism known as
plugins.
The plugins are nodes inserted in the network graph definition that map to user-defined
GPU kernels. TensorRT-LLM uses a number of such plugins. They can be found in
-the cpp/tensorrt_llm/plugins directory.
+the cpp/tensorrt_llm/plugins directory.
Plugins are written in C++ and follow a well-defined interface described in the
Extending TensorRT with Custom Layers
section of the TensorRT
Developer Guide.
When executed within a TensorRT engine, plugins trigger the execution of
their encapsulated GPU kernels. A fairly simple example of plugins is the
-QuantizeTensorPlugin that
+QuantizeTensorPlugin that
triggers a CUDA kernel in the QuantizeTensorPlugin::enqueue member function:
// In cpp/tensorrt_llm/plugins/quantizeTensorPlugin/quantizeTensorPlugin.cpp:
@@ -715,7 +715,7 @@ using TensorRT plugins that wrap communication primitives from the
plugin that optimize the All-Reduce primitive in the presence of All-to-all
connections between GPUs (through NVSwitch in DGX systems).
The communication plugins can be found in
-cpp/tensorrt_llm/plugins/ncclPlugin
+cpp/tensorrt_llm/plugins/ncclPlugin
and the multi-GPU functions are exposed in the TensorRT-LLM Model Definition API
as:
# In tensorrt_llm/functional.py:
@@ -1002,9 +1002,9 @@ srun \
diff --git a/legacy/architecture/model-weights-loader.html b/legacy/architecture/model-weights-loader.html
index 5dd1c45207..a7975f3721 100644
--- a/legacy/architecture/model-weights-loader.html
+++ b/legacy/architecture/model-weights-loader.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -940,9 +940,9 @@ The support for Qwen-1 is in
diff --git a/legacy/architecture/workflow.html b/legacy/architecture/workflow.html
index d6bc4432ac..b1b9510dec 100644
--- a/legacy/architecture/workflow.html
+++ b/legacy/architecture/workflow.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -828,9 +828,9 @@ The usage of this API looks like this:
diff --git a/legacy/dev-on-cloud/build-image-to-dockerhub.html b/legacy/dev-on-cloud/build-image-to-dockerhub.html
index 05100efc08..dfeb6d792c 100644
--- a/legacy/dev-on-cloud/build-image-to-dockerhub.html
+++ b/legacy/dev-on-cloud/build-image-to-dockerhub.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -686,9 +686,9 @@ docker push <your_dockerhub_use
diff --git a/legacy/dev-on-cloud/dev-on-runpod.html b/legacy/dev-on-cloud/dev-on-runpod.html
index 823315209a..7b1816ed02 100644
--- a/legacy/dev-on-cloud/dev-on-runpod.html
+++ b/legacy/dev-on-cloud/dev-on-runpod.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -686,9 +686,9 @@
diff --git a/legacy/key-features.html b/legacy/key-features.html
index ec5e004bec..8682083b0b 100644
--- a/legacy/key-features.html
+++ b/legacy/key-features.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -628,9 +628,9 @@
diff --git a/legacy/performance/perf-analysis.html b/legacy/performance/perf-analysis.html
index 2cf4d13d6e..946e720610 100644
--- a/legacy/performance/perf-analysis.html
+++ b/legacy/performance/perf-analysis.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -744,9 +744,9 @@ python3 benchmarks/cpp/prepare_dataset.py
diff --git a/legacy/performance/perf-benchmarking.html b/legacy/performance/perf-benchmarking.html
index b8090e1b1e..04861c5800 100644
--- a/legacy/performance/perf-benchmarking.html
+++ b/legacy/performance/perf-benchmarking.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -1584,9 +1584,9 @@ The choices are specified with a YAML file like the following example (
diff --git a/legacy/performance/performance-tuning-guide/benchmarking-default-performance.html b/legacy/performance/performance-tuning-guide/benchmarking-default-performance.html
index 29522d64dc..96f825e252 100644
--- a/legacy/performance/performance-tuning-guide/benchmarking-default-performance.html
+++ b/legacy/performance/performance-tuning-guide/benchmarking-default-performance.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -893,9 +893,9 @@ P99: 1.00
diff --git a/legacy/performance/performance-tuning-guide/deciding-model-sharding-strategy.html b/legacy/performance/performance-tuning-guide/deciding-model-sharding-strategy.html
index f92c130e7f..70c8cd10c6 100644
--- a/legacy/performance/performance-tuning-guide/deciding-model-sharding-strategy.html
+++ b/legacy/performance/performance-tuning-guide/deciding-model-sharding-strategy.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -672,9 +672,9 @@
diff --git a/legacy/performance/performance-tuning-guide/fp8-quantization.html b/legacy/performance/performance-tuning-guide/fp8-quantization.html
index 0218194711..c78aadc5a6 100644
--- a/legacy/performance/performance-tuning-guide/fp8-quantization.html
+++ b/legacy/performance/performance-tuning-guide/fp8-quantization.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -1004,9 +1004,9 @@ accuracy loss is unacceptable.
diff --git a/legacy/performance/performance-tuning-guide/index.html b/legacy/performance/performance-tuning-guide/index.html
index 76fdfc93cc..69e642142b 100644
--- a/legacy/performance/performance-tuning-guide/index.html
+++ b/legacy/performance/performance-tuning-guide/index.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -666,9 +666,9 @@
diff --git a/legacy/performance/performance-tuning-guide/introduction.html b/legacy/performance/performance-tuning-guide/introduction.html
index 80617aac77..8d06aeac7c 100644
--- a/legacy/performance/performance-tuning-guide/introduction.html
+++ b/legacy/performance/performance-tuning-guide/introduction.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -655,9 +655,9 @@
diff --git a/legacy/performance/performance-tuning-guide/tuning-max-batch-size-and-max-num-tokens.html b/legacy/performance/performance-tuning-guide/tuning-max-batch-size-and-max-num-tokens.html
index 0d4ea2fd79..5aaabbf00a 100644
--- a/legacy/performance/performance-tuning-guide/tuning-max-batch-size-and-max-num-tokens.html
+++ b/legacy/performance/performance-tuning-guide/tuning-max-batch-size-and-max-num-tokens.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -854,9 +854,9 @@
diff --git a/legacy/performance/performance-tuning-guide/useful-build-time-flags.html b/legacy/performance/performance-tuning-guide/useful-build-time-flags.html
index a401cac934..8a023b7a0b 100644
--- a/legacy/performance/performance-tuning-guide/useful-build-time-flags.html
+++ b/legacy/performance/performance-tuning-guide/useful-build-time-flags.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -917,9 +917,9 @@ This can be enabled via the LLM-API as such
diff --git a/legacy/performance/performance-tuning-guide/useful-runtime-flags.html b/legacy/performance/performance-tuning-guide/useful-runtime-flags.html
index 3b79fd8f54..23a6c1a13f 100644
--- a/legacy/performance/performance-tuning-guide/useful-runtime-flags.html
+++ b/legacy/performance/performance-tuning-guide/useful-runtime-flags.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -840,9 +840,9 @@ via KVCacheConfig
diff --git a/legacy/python-api/tensorrt_llm.functional.html b/legacy/python-api/tensorrt_llm.functional.html
index 0145aa492d..3a4799a27c 100644
--- a/legacy/python-api/tensorrt_llm.functional.html
+++ b/legacy/python-api/tensorrt_llm.functional.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -7038,9 +7038,9 @@ The index for rebuilding the sequence
diff --git a/legacy/python-api/tensorrt_llm.layers.html b/legacy/python-api/tensorrt_llm.layers.html
index 82acd2d172..f23efd90e6 100644
--- a/legacy/python-api/tensorrt_llm.layers.html
+++ b/legacy/python-api/tensorrt_llm.layers.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -2589,9 +2589,9 @@ the number of tokens used for each task, should be equal to prompt_embedding_tab
diff --git a/legacy/python-api/tensorrt_llm.models.html b/legacy/python-api/tensorrt_llm.models.html
index cc7ef04a2e..652fbb14eb 100644
--- a/legacy/python-api/tensorrt_llm.models.html
+++ b/legacy/python-api/tensorrt_llm.models.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -3644,9 +3644,9 @@ ranges of the dimensions of when using TRT dynamic shapes.
diff --git a/legacy/python-api/tensorrt_llm.plugin.html b/legacy/python-api/tensorrt_llm.plugin.html
index 5752c45940..25d7f7382d 100644
--- a/legacy/python-api/tensorrt_llm.plugin.html
+++ b/legacy/python-api/tensorrt_llm.plugin.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -1655,9 +1655,9 @@ migrated to the centralized building script tensorrt_llm/commands/build.py
diff --git a/legacy/python-api/tensorrt_llm.quantization.html b/legacy/python-api/tensorrt_llm.quantization.html
index 60c9f2295d..0b53f55c4c 100644
--- a/legacy/python-api/tensorrt_llm.quantization.html
+++ b/legacy/python-api/tensorrt_llm.quantization.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -717,9 +717,9 @@ the quantized model as TRT-LLM checkpoint
diff --git a/legacy/python-api/tensorrt_llm.runtime.html b/legacy/python-api/tensorrt_llm.runtime.html
index fb569a99ba..61b69f9333 100644
--- a/legacy/python-api/tensorrt_llm.runtime.html
+++ b/legacy/python-api/tensorrt_llm.runtime.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -3286,9 +3286,9 @@ mrope_position_deltas (torch.Tensor of shape (batch_size)
diff --git a/legacy/reference/memory.html b/legacy/reference/memory.html
index e4bca41fb6..c6471cd66e 100644
--- a/legacy/reference/memory.html
+++ b/legacy/reference/memory.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -574,8 +574,8 @@ Here some explanations on how these values affect the memory:
Memory pool#
-TensorRT-LLM C++ runtime is using stream-ordered memory allocator to allocate and free buffers, see BufferManager::initMemoryPool, which uses the default memory pool managed by the CUDA driver. When a TrtGptModel object is destroyed, memory is returned to the memory pool and can be reused by the next instance of a TrtGptModel object. Memory will be released from the pool if it is required for other memory allocations.
-However, nvidia-smi may still show high memory occupation after memory is returned to the CUDA driver’s memory pool. This should not be a concern and is intended behavior. The amount of reserved and free memory in the pool can be inspected by BufferManager::memoryPoolReserved()) and BufferManager::memoryPoolFree()), respectively.
+TensorRT-LLM C++ runtime is using stream-ordered memory allocator to allocate and free buffers, see BufferManager::initMemoryPool, which uses the default memory pool managed by the CUDA driver. When a TrtGptModel object is destroyed, memory is returned to the memory pool and can be reused by the next instance of a TrtGptModel object. Memory will be released from the pool if it is required for other memory allocations.
+However, nvidia-smi may still show high memory occupation after memory is returned to the CUDA driver’s memory pool. This should not be a concern and is intended behavior. The amount of reserved and free memory in the pool can be inspected by BufferManager::memoryPoolReserved()) and BufferManager::memoryPoolFree()), respectively.
Known Issues#
@@ -766,9 +766,9 @@ Here some explanations on how these values affect the memory:
diff --git a/legacy/reference/multimodal-feature-support-matrix.html b/legacy/reference/multimodal-feature-support-matrix.html
index f26350304f..54bde73e81 100644
--- a/legacy/reference/multimodal-feature-support-matrix.html
+++ b/legacy/reference/multimodal-feature-support-matrix.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -686,9 +686,9 @@
diff --git a/legacy/reference/precision.html b/legacy/reference/precision.html
index 4fed9331e1..298e907245 100644
--- a/legacy/reference/precision.html
+++ b/legacy/reference/precision.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -577,7 +577,7 @@ maintaining the accuracy of the network (on downstream tasks).
weights of the model. TensorRT-LLM includes scripts to prepare the model to
run using the SmoothQuant method.
Examples of how to enable SmoothQuant for GPT, GPT-J and LLaMA can be found in
-the examples/quantization folder of that release.
+the examples/quantization folder of that release.
INT4 and INT8 Weight-Only (W4A16 and W8A16)#
@@ -586,8 +586,8 @@ a model and dequantizing those weights on-the-fly in linear layers (Matmuls).
The activations are encoded using floating-point values (FP16 or BF16).
To use INT4/INT8 Weight-Only methods, the user must determine the scaling
factors to use to quantize and dequantize the weights of the model.
-
+
GPTQ and AWQ (W4A16)#
@@ -597,19 +597,19 @@ and
https://arxiv.org/abs/2306.00978,
respectively. TensorRT-LLM supports per-group scaling factors and
zero-offsetting in linear layers to implement GPTQ and AWQ methods. See the
-WeightOnlyGroupwiseQuantMatmulPlugin
+WeightOnlyGroupwiseQuantMatmulPlugin
plugin and the corresponding
-weight_only_groupwise_quant_matmul
+weight_only_groupwise_quant_matmul
Python function, for details.
-This release includes examples of applying GPTQ to GPT-NeoX
-and LLaMA-v2, as well as an example of using AWQ with
-GPT-J.
+This release includes examples of applying GPTQ to GPT-NeoX
+and LLaMA-v2, as well as an example of using AWQ with
+GPT-J.
FP8 (Hopper)#
This release of TensorRT-LLM contains implementations of FP8 for GPT-NeMo,
GPT-J and LLaMA. Those examples can be found in
-examples/quantization.
+examples/quantization.
NVFP4 (Blackwell)#
@@ -1111,7 +1111,7 @@ The language component decides which quantization methods are supported by a giv
Technical Detail: The QuantMode Flags#
The quantization method is controlled by the
-QuantMode flags. The different fields
+QuantMode flags. The different fields
are:
INT4_WEIGHTS, the weights are quantized to 4 bits (W4A*),
@@ -1261,9 +1261,9 @@ are:
diff --git a/legacy/reference/support-matrix.html b/legacy/reference/support-matrix.html
index 9cf9643a82..a6cec95924 100644
--- a/legacy/reference/support-matrix.html
+++ b/legacy/reference/support-matrix.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -975,9 +975,9 @@ In addition, older architectures can have limitations for newer software release
diff --git a/legacy/reference/troubleshooting.html b/legacy/reference/troubleshooting.html
index 7393c73854..9dfaa0de05 100644
--- a/legacy/reference/troubleshooting.html
+++ b/legacy/reference/troubleshooting.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -952,9 +952,9 @@ dedicated MPI environment, not the one provided by your Slurm allocation.
diff --git a/legacy/tensorrt_quickstart.html b/legacy/tensorrt_quickstart.html
index 2d144df1a6..db7304c6b2 100644
--- a/legacy/tensorrt_quickstart.html
+++ b/legacy/tensorrt_quickstart.html
@@ -61,7 +61,7 @@
@@ -75,7 +75,7 @@
-
+
@@ -672,9 +672,9 @@
diff --git a/legacy/torch.html b/legacy/torch.html
index 0189495af1..37b49e783b 100644
--- a/legacy/torch.html
+++ b/legacy/torch.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -691,9 +691,9 @@ This feature is currently in beta, and the related API is subjected to change in
diff --git a/llm-api/index.html b/llm-api/index.html
index ddb7288e89..25232c5d7f 100644
--- a/llm-api/index.html
+++ b/llm-api/index.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -782,9 +782,9 @@
diff --git a/llm-api/reference.html b/llm-api/reference.html
index 280aea561b..306101522e 100644
--- a/llm-api/reference.html
+++ b/llm-api/reference.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -611,7 +611,7 @@
batch_wait_timeout_iters (int) – prototype Maximum number of iterations the scheduler will wait to accumulate new coming requests for improved GPU utilization efficiency. If greater than 0, the scheduler will delay batch processing to gather more requests up to the specified iteration limit. If 0, disables timeout-iters-based batching delays. Defaults to 0.
batch_wait_max_tokens_ratio (float) – prototype Token accumulation threshold ratio for batch scheduling optimization. If greater than 0, the scheduler will accumulate requests locally until the total token count reaches batch_wait_max_tokens_ratio * max_num_tokens. This mechanism enhances GPU utilization efficiency by ensuring adequate batch sizes.If 0 disables token-based batching delays. Defaults to 0.
torch_compile_config (Optional[tensorrt_llm.llmapi.llm_args.TorchCompileConfig]) – prototype Torch compile config. Defaults to None.
-enable_autotuner (bool) – prototype Enable autotuner only when torch compile is enabled. Defaults to True.
+enable_autotuner (bool) – prototype Enable autotuner for all tunable ops. This flag is for debugging purposes only, and the performance may significantly degrade if set to false. Defaults to True.
enable_layerwise_nvtx_marker (bool) – beta If true, enable layerwise nvtx marker. Defaults to False.
enable_min_latency (bool) – beta If true, enable min-latency mode. Currently only used for Llama4. Defaults to False.
stream_interval (int) – stable The iteration interval to create responses under the streaming mode. Set this to a larger value when the batch size is large, which helps reduce the streaming overhead. Defaults to 1.
@@ -5352,7 +5352,7 @@ a subset of the possible backends.
-
-validator validate_positive_values » max_window_size, max_ngram_size, max_verification_set_size[source]#
+validator validate_positive_values » max_window_size, max_verification_set_size, max_ngram_size[source]#
@@ -17497,7 +17497,7 @@ If checkpoint_format and checkpoint_loader are both provided, checkpoint_loader
-
field enable_autotuner: bool = True#
-prototype Enable autotuner only when torch compile is enabled.
+prototype Enable autotuner for all tunable ops. This flag is for debugging purposes only, and the performance may significantly degrade if set to false.
@@ -24315,9 +24315,9 @@ a subset of the possible backends.
diff --git a/models/adding-new-model.html b/models/adding-new-model.html
index f73e4679b7..7e42d06236 100644
--- a/models/adding-new-model.html
+++ b/models/adding-new-model.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -869,9 +869,9 @@
diff --git a/models/supported-models.html b/models/supported-models.html
index ebb7b52ec9..c9009c791f 100644
--- a/models/supported-models.html
+++ b/models/supported-models.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -1012,9 +1012,9 @@
diff --git a/objects.inv b/objects.inv
index 237dcebeaed88d0e3719615f1c09ff9f3b206ff7..0f58aceea5716ed651fa5e267e70bd0f99c67505 100644
GIT binary patch
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diff --git a/overview.html b/overview.html
index 58f1a7694b..da4988428e 100644
--- a/overview.html
+++ b/overview.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -525,7 +525,7 @@
🔥 Architected on Pytorch#
TensorRT LLM provides a high-level Python LLM API that supports a wide range of inference setups - from single-GPU to multi-GPU or multi-node deployments. It includes built-in support for various parallelism strategies and advanced features. The LLM API integrates seamlessly with the broader inference ecosystem, including NVIDIA Dynamo and the Triton Inference Server.
-TensorRT LLM is designed to be modular and easy to modify. Its PyTorch-native architecture allows developers to experiment with the runtime or extend functionality. Several popular models are also pre-defined and can be customized using native PyTorch code, making it easy to adapt the system to specific needs.
+TensorRT LLM is designed to be modular and easy to modify. Its PyTorch-native architecture allows developers to experiment with the runtime or extend functionality. Several popular models are also pre-defined and can be customized using native PyTorch code, making it easy to adapt the system to specific needs.
⚡ State-of-the-Art Performance#
@@ -741,9 +741,9 @@
diff --git a/py-modindex.html b/py-modindex.html
index cfdd9692a9..c99d8400a0 100644
--- a/py-modindex.html
+++ b/py-modindex.html
@@ -60,7 +60,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -682,9 +682,9 @@
diff --git a/quick-start-guide.html b/quick-start-guide.html
index 48c5eec705..5b2829a341 100644
--- a/quick-start-guide.html
+++ b/quick-start-guide.html
@@ -61,7 +61,7 @@
@@ -76,7 +76,7 @@
-
+
@@ -520,7 +520,7 @@
Launch Docker Container#
The TensorRT LLM container maintained by NVIDIA contains all of the required dependencies pre-installed. You can start the container on a machine with NVIDIA GPUs via:
-docker run --rm -it --ipc host --gpus all --ulimit memlock=-1 --ulimit stack=67108864 -p 8000:8000 nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc3
+docker run --rm -it --ipc host --gpus all --ulimit memlock=-1 --ulimit stack=67108864 -p 8000:8000 nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc4
@@ -799,9 +799,9 @@ To learn more about the LLM API, check out the
diff --git a/release-notes.html b/release-notes.html
index 2c1fb340b4..926edf9095 100644
--- a/release-notes.html
+++ b/release-notes.html
@@ -61,7 +61,7 @@
@@ -74,7 +74,7 @@
-
+
@@ -2451,9 +2451,9 @@
diff --git a/search.html b/search.html
index d811a6ae59..9f51d9db58 100644
--- a/search.html
+++ b/search.html
@@ -61,7 +61,7 @@
@@ -82,7 +82,7 @@
-
+
@@ -627,9 +627,9 @@
diff --git a/searchindex.js b/searchindex.js
index 3b17fd27f8..9ce30c1d9a 100644
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
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Latency Boundaries: Optimizing DeepSeek-R1 Performance on NVIDIA B200 GPUs": [[13, null]], "PyExecutor": [[157, "pyexecutor"]], "PyTorch Backend": [[148, null]], "Python Bindings for the Executor API": [[106, "python-bindings-for-the-executor-api"]], "Python Interface": [[16, "python-interface"]], "Python runtime (Not recommended to be used)": [[142, "python-runtime-not-recommended-to-be-used"]], "Quantization": [[45, "quantization"], [95, null], [140, null], [170, null]], "Quantization APIs": [[122, "quantization-apis"]], "Quantization and Dequantization (Q/DQ)": [[144, "quantization-and-dequantization-q-dq"]], "Quantization in TensorRT LLM": [[95, "quantization-in-tensorrt-llm"]], "Quantization in TensorRT-LLM": [[7, "quantization-in-tensorrt-llm"]], "Quantization in the PyTorch Flow": [[40, "quantization-in-the-pytorch-flow"], [127, "quantization-in-the-pytorch-flow"]], "Quantized KV-Cache": [[130, "quantized-kv-cache"]], "Quick Health Check": [[9, "quick-health-check"]], "Quick Links": [[95, "quick-links"], [100, null]], "Quick Start": [[98, "quick-start"], [148, "quick-start"]], "Quick Start Example": [[149, "quick-start-example"]], "Quick Start Guide": [[154, null]], "Quick Start for Popular Models": [[33, "quick-start-for-popular-models"]], "Quick start": [[91, "quick-start"], [163, "quick-start"]], "Quickstart": [[127, "quickstart"]], "Qwen 3": [[17, "qwen-3"]], "Qwen3-235B-A22B": [[41, "qwen3-235b-a22b"]], "Qwen3-30B-A3B": [[41, "qwen3-30b-a3b"]], "Rank Weights": [[119, "rank-weights"]], "Ray Orchestrator (Prototype)": [[96, null]], "Re-balanced the sparse experts": [[13, "re-balanced-the-sparse-experts"]], "Re-inplace Optimization": [[99, "re-inplace-optimization"]], "ReDrafter": [[116, "redrafter"]], "Recommended Performance Settings": [[28, "recommended-performance-settings"], [29, "recommended-performance-settings"], [30, "recommended-performance-settings"], [31, "recommended-performance-settings"], [32, "recommended-performance-settings"]], "Recompilation": [[99, "recompilation"]], "Reduce Binding and Inter-Process Communication Overhead": [[20, "reduce-binding-and-inter-process-communication-overhead"]], "Reduce Norm Fusion Plugin for Llama models:": [[134, "reduce-norm-fusion-plugin-for-llama-models"]], "Reduce Norm Fusion with User Buffers for Llama Models": [[130, "reduce-norm-fusion-with-user-buffers-for-llama-models"]], "Reference": [[11, "reference"], [118, "reference"]], "References": [[92, "references"], [94, "references"], [169, "references"]], "Relative Attention Bias (RAB)": [[108, "relative-attention-bias-rab"]], "Relax Acceptance Verification": [[13, "relax-acceptance-verification"]], "Relaxed Acceptance": [[14, "relaxed-acceptance"]], "Release Notes": [[155, null]], "Reproducing Benchmarked Results": [[41, "reproducing-benchmarked-results"]], "Reproducing Steps": [[17, "reproducing-steps"]], "Reproducing steps": [[2, "reproducing-steps"], [16, "reproducing-steps"]], "Request Additional Output": [[106, "request-additional-output"]], "Request Time Breakdown": [[26, "request-time-breakdown"]], "ResourceManager": [[157, "resourcemanager"]], "Results": [[128, "results"]], "Retention Policy": [[88, "retention-policy"]], "Rethink network structure": [[12, "rethink-network-structure"]], "Reuse Across Requests": [[88, "reuse-across-requests"]], "Revisiting Paged Context Attention and Context Chunking": [[93, "revisiting-paged-context-attention-and-context-chunking"], [133, "revisiting-paged-context-attention-and-context-chunking"]], "Roadmap": [[83, "roadmap"], [96, "roadmap"], [165, "roadmap"]], "Rotary Positional Embedding (RoPE)": [[77, "rotary-positional-embedding-rope"], [108, "rotary-positional-embedding-rope"]], "RouterGEMM": [[13, "routergemm"]], "Run Docker Container": [[28, "run-docker-container"], [29, "run-docker-container"], [30, "run-docker-container"], [31, "run-docker-container"], [32, "run-docker-container"]], "Run LLM-API with pytorch backend on Slurm": [[62, null]], "Run Offline Inference with LLM API": [[154, "run-offline-inference-with-llm-api"]], "Run benchmarking with trtllm-serve": [[26, null]], "Run gpt-2b + LoRA using Executor / cpp runtime": [[113, null]], "Run the benchmark": [[26, "run-the-benchmark"]], "Run trtllm-bench": [[90, "run-trtllm-bench"], [168, "run-trtllm-bench"]], "Run trtllm-bench with pytorch backend on Slurm": [[63, null]], "Run trtllm-serve with pytorch backend on Slurm": [[64, null]], "Run with trtllm-bench": [[91, "run-with-trtllm-bench"]], "Running Evaluations to Verify Accuracy (Optional)": [[28, "running-evaluations-to-verify-accuracy-optional"], [29, "running-evaluations-to-verify-accuracy-optional"], [30, "running-evaluations-to-verify-accuracy-optional"], [31, "running-evaluations-to-verify-accuracy-optional"]], "Running GPT-OSS-120B with Eagle3 Speculative Decoding on GB200/B200 (TensorRT LLM)": [[9, null]], "Running Pre-quantized Models": [[95, "running-pre-quantized-models"]], "Running Tests": [[34, "running-tests"]], "Running Throughput and Latency Benchmarks": [[128, "running-throughput-and-latency-benchmarks"]], "Running With Weight Streaming to Reduce GPU Memory Consumption": [[117, null]], "Running a High Performance GPT-OSS-120B Inference Server with TensorRT LLM": [[21, null]], "Running multi-modal models in the PyTorch Workflow": [[40, "running-multi-modal-models-in-the-pytorch-workflow"], [127, "running-multi-modal-models-in-the-pytorch-workflow"]], "Running the Benchmark": [[41, "running-the-benchmark"]], "Running the TensorRT LLM Server": [[21, "running-the-tensorrt-llm-server"]], "Running with the PyTorch Workflow": [[40, "running-with-the-pytorch-workflow"], [127, "running-with-the-pytorch-workflow"]], "Runtime": [[1, null], [120, "runtime"], [141, null]], "Runtime Configuration Examples": [[66, null]], "Runtime Customization": [[45, "runtime-customization"]], "Runtime Integrations": [[84, "runtime-integrations"], [166, "runtime-integrations"]], "Runtime Optimizations": [[15, "runtime-optimizations"], [38, "runtime-optimizations"]], "RuntimeError: only rank 0 can start multi-node session, got 1": [[149, "runtimeerror-only-rank-0-can-start-multi-node-session-got-1"]], "Sample Chat Completions Request": [[9, "sample-chat-completions-request"]], "Sampling": [[45, "sampling"], [97, null], [171, null]], "Sampling Parameters": [[109, "sampling-parameters"]], "Sampling Techniques Showcase": [[67, null]], "ScaffoldingLlm": [[11, "scaffoldingllm"]], "Scaling Expert Parallelism in TensorRT LLM (Part 1: Design and Implementation of Large-scale EP)": [[16, null]], "Scaling Expert Parallelism in TensorRT LLM (Part 2: Performance Status and Optimization)": [[20, null]], "Scaling Expert Parallelism in TensorRT LLM (Part 3: Pushing the Performance Boundary)": [[12, null]], "Scaling factor(s)": [[77, "scaling-factor-s"], [108, "scaling-factor-s"]], "Scheduler": [[157, "scheduler"], [173, null]], "Scheduler Introduction": [[173, "scheduler-introduction"]], "Scheduling Strategies for Load Balancing": [[8, "scheduling-strategies-for-load-balancing"]], "Seamless Model Deployment from PyTorch to TensorRT LLM": [[83, "seamless-model-deployment-from-pytorch-to-tensorrt-llm"]], "Seamless Model Deployment from PyTorch to TensorRT-LLM": [[165, "seamless-model-deployment-from-pytorch-to-tensorrt-llm"]], "See also": [[163, "see-also"]], "Selecting Triton as the MoE backend": [[21, "selecting-triton-as-the-moe-backend"], [21, "id3"]], "Sender and Receiver": [[37, "sender-and-receiver"]], "Sending Requests with Different Beam Widths": [[106, "sending-requests-with-different-beam-widths"]], "Serving with trtllm-serve": [[163, null]], "Set power limits": [[40, "set-power-limits"], [127, "set-power-limits"]], "Setting": [[8, "setting"]], "Setting up Multimodal Serving": [[26, "setting-up-multimodal-serving"]], "Show code": [[28, null], [28, null], [29, null], [29, null], [30, null], [31, null], [32, null]], "Single LoRA Adapter": [[90, "single-lora-adapter"], [168, "single-lora-adapter"]], "Single node hanging when using docker run --net=host": [[149, "single-node-hanging-when-using-docker-run-net-host"]], "Situations that can prevent kv cache reuse": [[112, "situations-that-can-prevent-kv-cache-reuse"]], "Sliding Window Attention": [[89, "sliding-window-attention"]], "Sliding Window Attention, Cyclic (Rolling Buffer) KV Cache": [[77, "sliding-window-attention-cyclic-rolling-buffer-kv-cache"], [108, "sliding-window-attention-cyclic-rolling-buffer-kv-cache"]], "Slurm": [[53, "slurm"]], "Smart Router": [[13, "smart-router"]], "Software": [[145, "software"]], "Sparse Attention": [[68, null]], "Sparse Experts as GEMMs (only works when moe_backend=CUTLASS)": [[13, "sparse-experts-as-gemms-only-works-when-moe-backend-cutlass"]], "Speculative Decoding": [[10, "speculative-decoding"], [69, null], [88, "speculative-decoding"], [98, null]], "Speculative Sampling": [[116, null]], "Speculative decoding arguments": [[23, "tensorrt_llm.commands.build-parse_arguments-speculative-decoding-arguments"]], "Speed up inference with SOTA quantization techniques in TRT-LLM": [[7, null]], "Speed-up for the First Turn": [[19, "speed-up-for-the-first-turn"]], "Start the TensorRT LLM Container": [[9, "start-the-tensorrt-llm-container"]], "Start the trtllm-serve service": [[26, "start-the-trtllm-serve-service"]], "Starting a Server": [[27, "starting-a-server"]], "Starting the Server": [[90, "starting-the-server"], [168, "starting-the-server"]], "Step 1. Write Modeling Part": [[118, "step-1-write-modeling-part"]], "Step 1: Clone the repository": [[18, "step-1-clone-the-repository"]], "Step 1: Create the Checkpoint Loader": [[85, "step-1-create-the-checkpoint-loader"], [167, "step-1-create-the-checkpoint-loader"]], "Step 1: Run inference and collect statistics": [[16, "step-1-run-inference-and-collect-statistics"]], "Step 2. Implement Weight Conversion": [[118, "step-2-implement-weight-conversion"]], "Step 2: Create the Checkpoint Weight Loader": [[85, "step-2-create-the-checkpoint-weight-loader"], [167, "step-2-create-the-checkpoint-weight-loader"]], "Step 2: Generate the EPLB configuration": [[16, "step-2-generate-the-eplb-configuration"]], "Step 2: Prepare the TensorRT LLM release Docker image": [[18, "step-2-prepare-the-tensorrt-llm-release-docker-image"]], "Step 3. Register New Model": [[118, "step-3-register-new-model"]], "Step 3: (Optional) Tag and push the Docker image to your registry": [[18, "step-3-optional-tag-and-push-the-docker-image-to-your-registry"]], "Step 3: Create the Checkpoint Config Loader": [[85, "step-3-create-the-checkpoint-config-loader"], [167, "step-3-create-the-checkpoint-config-loader"]], "Step 3: Run inference with the EPLB configuration": [[16, "step-3-run-inference-with-the-eplb-configuration"]], "Step 4. Verify New Model": [[118, "step-4-verify-new-model"]], "Step 4: Create the Checkpoint Weight Mapper": [[85, "step-4-create-the-checkpoint-weight-mapper"], [167, "step-4-create-the-checkpoint-weight-mapper"]], "Step 4: Start the TensorRT LLM server": [[18, "step-4-start-the-tensorrt-llm-server"]], "Step 5: Test the server with a sample request": [[18, "step-5-test-the-server-with-a-sample-request"]], "Step 6: (Optional) Monitor server logs": [[18, "step-6-optional-monitor-server-logs"]], "Step 7: (Optional) Stop the server": [[18, "step-7-optional-stop-the-server"]], "Step-by-Step Guide": [[151, "step-by-step-guide"], [156, "step-by-step-guide"]], "StreamingLLM": [[77, "streamingllm"], [108, "streamingllm"]], "Structured output with guided decoding": [[106, "structured-output-with-guided-decoding"]], "Summary": [[127, "summary"]], "Summary of Configuration Option Recommendations:": [[130, "summary-of-configuration-option-recommendations"], [134, "summary-of-configuration-option-recommendations"]], "Support Matrix": [[83, "support-matrix"], [84, null], [145, null], [165, "support-matrix"], [166, null]], "Support Models": [[84, "support-models"], [166, "support-models"]], "Support Stream Interval": [[20, "support-stream-interval"]], "Support matrix": [[144, "support-matrix"]], "Supported C++ Header Files": [[101, "supported-c-header-files"]], "Supported Models": [[152, null]], "Supported Quantization Modes": [[40, "supported-quantization-modes"], [127, "supported-quantization-modes"]], "Syntax": [[24, "syntax"], [27, "syntax"]], "System Level optimizations": [[13, "system-level-optimizations"]], "TRTLLM Backend": [[13, "trtllm-backend"]], "TRTLLM bench with LORA": [[90, "trtllm-bench-with-lora"], [168, "trtllm-bench-with-lora"]], "TRTLLM serve with LoRA": [[90, "trtllm-serve-with-lora"], [168, "trtllm-serve-with-lora"]], "Table of Contents": [[2, "table-of-contents"], [8, "table-of-contents"], [10, "table-of-contents"], [11, "table-of-contents"], [12, "table-of-contents"], [13, "table-of-contents"], [14, "table-of-contents"], [15, "table-of-contents"], [16, "table-of-contents"], [19, "table-of-contents"], [20, "table-of-contents"], [35, "table-of-contents"], [37, "table-of-contents"], [85, "table-of-contents"], [90, "table-of-contents"], [99, "table-of-contents"], [131, "table-of-contents"], [132, "table-of-contents"], [151, "table-of-contents"], [156, "table-of-contents"], [167, "table-of-contents"], [168, "table-of-contents"]], "Target Model": [[10, "target-model"]], "Technical Detail: The QuantMode Flags": [[144, "technical-detail-the-quantmode-flags"]], "Tensor Parallel vs Expert Parallel": [[107, "tensor-parallel-vs-expert-parallel"]], "Tensor Parallelism (TP)": [[94, "tensor-parallelism-tp"], [94, "id1"]], "Tensor-Related Methods": [[110, "tensor-related-methods"]], "TensorRT Compiler": [[120, "tensorrt-compiler"]], "TensorRT LLM Benchmarking": [[40, null]], "TensorRT LLM Checkpoint": [[119, null]], "TensorRT LLM Custom Backend": [[99, "tensorrt-llm-custom-backend"]], "TensorRT-LLM Benchmarking": [[127, null]], "TensorRT-LLM Build Workflow": [[122, null]], "TensorRT-LLM Model Weights Loader": [[121, null]], "TensorRT-LLM Release 0.10.0": [[155, "tensorrt-llm-release-0-10-0"]], "TensorRT-LLM Release 0.11.0": [[155, "tensorrt-llm-release-0-11-0"]], "TensorRT-LLM Release 0.12.0": [[155, "tensorrt-llm-release-0-12-0"]], "TensorRT-LLM Release 0.13.0": [[155, "tensorrt-llm-release-0-13-0"]], "TensorRT-LLM Release 0.14.0": [[155, "tensorrt-llm-release-0-14-0"]], "TensorRT-LLM Release 0.15.0": [[155, "tensorrt-llm-release-0-15-0"]], "TensorRT-LLM Release 0.16.0": [[155, "tensorrt-llm-release-0-16-0"]], "TensorRT-LLM Release 0.17.0": [[155, "tensorrt-llm-release-0-17-0"]], "TensorRT-LLM Release 0.18.0": [[155, "tensorrt-llm-release-0-18-0"]], "TensorRT-LLM Release 0.18.1": [[155, "tensorrt-llm-release-0-18-1"]], "TensorRT-LLM Release 0.18.2": [[155, "tensorrt-llm-release-0-18-2"]], "TensorRT-LLM Release 0.19.0": [[155, "tensorrt-llm-release-0-19-0"]], "TensorRT-LLM Release 0.20.0": [[155, "tensorrt-llm-release-0-20-0"]], "TensorRT-LLM Release 0.21.0": [[155, "tensorrt-llm-release-0-21-0"]], "TensorRT-LLM Release 0.7.1": [[155, "tensorrt-llm-release-0-7-1"]], "TensorRT-LLM Release 0.8.0": [[155, "tensorrt-llm-release-0-8-0"]], "TensorRT-LLM Release 0.9.0": [[155, "tensorrt-llm-release-0-9-0"]], "TensorRT-LLM Release 1.0": [[155, "tensorrt-llm-release-1-0"]], "Test definitions": [[35, "test-definitions"]], "Test the Server with a Sample Request": [[21, "test-the-server-with-a-sample-request"]], "Testing API Endpoint": [[28, "testing-api-endpoint"], [29, "testing-api-endpoint"], [30, "testing-api-endpoint"], [31, "testing-api-endpoint"], [32, "testing-api-endpoint"]], "The Basics": [[88, "the-basics"]], "The Executor Class": [[106, "the-executor-class"]], "The Features of the TrtllmAttention Backend": [[77, "the-features-of-the-trtllmattention-backend"]], "The Request Class": [[106, "the-request-class"]], "The Response Class": [[106, "the-response-class"]], "The Result Class": [[106, "the-result-class"]], "The effect of EP Load Balancer": [[16, "the-effect-of-ep-load-balancer"], [16, "id3"]], "The schedulers": [[93, "the-schedulers"]], "The \u201cProbe\u201d technique": [[11, "the-probe-technique"]], "Theoretical Analysis and Modeling": [[8, "theoretical-analysis-and-modeling"]], "Throughput Benchmarking": [[40, "throughput-benchmarking"], [127, "throughput-benchmarking"]], "Throughput Measurements": [[41, "throughput-measurements"]], "Time Per Output Token (TPOT) and Inter-Token Latency (ITL)": [[26, "time-per-output-token-tpot-and-inter-token-latency-itl"], [28, "time-per-output-token-tpot-and-inter-token-latency-itl"], [29, "time-per-output-token-tpot-and-inter-token-latency-itl"], [30, "time-per-output-token-tpot-and-inter-token-latency-itl"], [31, "time-per-output-token-tpot-and-inter-token-latency-itl"]], "Time to First Token (TTFT)": [[26, "time-to-first-token-ttft"], [28, "time-to-first-token-ttft"], [29, "time-to-first-token-ttft"], [30, "time-to-first-token-ttft"], [31, "time-to-first-token-ttft"]], "Tips": [[146, "tips"]], "Tips and Troubleshooting": [[149, "tips-and-troubleshooting"]], "Tips for Piecewise CUDA Graph": [[99, "tips-for-piecewise-cuda-graph"]], "Tokenizer Customization": [[45, "tokenizer-customization"]], "Tokens Per Second (TPS) or Output Token Throughput": [[26, "tokens-per-second-tps-or-output-token-throughput"], [28, "tokens-per-second-tps-or-output-token-throughput"], [29, "tokens-per-second-tps-or-output-token-throughput"], [30, "tokens-per-second-tps-or-output-token-throughput"], [31, "tokens-per-second-tps-or-output-token-throughput"]], "Top Level API": [[157, "top-level-api"]], "Topology Requirements": [[114, "topology-requirements"]], "Torch Compile & Piecewise CUDA Graph": [[99, null]], "Torch IR Optimization": [[99, "torch-ir-optimization"]], "Total Token Throughput": [[26, "total-token-throughput"], [28, "total-token-throughput"], [29, "total-token-throughput"], [30, "total-token-throughput"], [31, "total-token-throughput"]], "Trace Grammar State for Draft Token Proposal and Rejection": [[10, "trace-grammar-state-for-draft-token-proposal-and-rejection"]], "Tradeoff": [[92, "tradeoff"], [169, "tradeoff"]], "Transceiver": [[37, "transceiver"]], "Transfer Agent": [[37, "transfer-agent"]], "Translator": [[121, "translator"]], "Tree-based speculative decoding support": [[14, "tree-based-speculative-decoding-support"]], "Triggering CI Best Practices": [[35, "triggering-ci-best-practices"]], "Triggering Post-merge tests": [[35, "triggering-post-merge-tests"]], "Triton Inference Server": [[17, "triton-inference-server"]], "Trouble shooting": [[121, "trouble-shooting"]], "Troubleshooting": [[146, null]], "Troubleshooting Tips": [[18, "troubleshooting-tips"], [21, "troubleshooting-tips"], [28, "troubleshooting-tips"], [29, "troubleshooting-tips"], [30, "troubleshooting-tips"], [31, "troubleshooting-tips"], [32, "troubleshooting-tips"]], "Troubleshooting Tips and Pitfalls To Avoid": [[128, "troubleshooting-tips-and-pitfalls-to-avoid"]], "Troubleshooting and FAQ": [[86, "troubleshooting-and-faq"], [105, "troubleshooting-and-faq"]], "Troubleshooting: Data Race between Host and CUDA Callback": [[10, "troubleshooting-data-race-between-host-and-cuda-callback"]], "Troubleshooting: Deadlock by GIL and CUDA Mutex": [[10, "troubleshooting-deadlock-by-gil-and-cuda-mutex"]], "Tuning Case Study": [[133, "tuning-case-study"], [133, "id2"]], "Tuning Max Batch Size": [[133, "tuning-max-batch-size"]], "Tuning Max Batch Size and Max Num Tokens": [[133, null]], "Tuning Max Num Tokens": [[133, "tuning-max-num-tokens"]], "Two Challenges": [[10, "two-challenges"]], "Two Model Speculative Decoding Architecture": [[98, "two-model-speculative-decoding-architecture"]], "Types of Events": [[111, "types-of-events"]], "Understand inference time GPU memory 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