[None][doc] Adding GPT-OSS Deployment Guide documentation #6637
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📝 WalkthroughWalkthroughA new technical blog post was added, providing a comprehensive step-by-step guide for deploying the GPT-OSS-120B inference server using NVIDIA TensorRT-LLM. The document covers prerequisites, container setup, deployment scenarios, configuration, testing, troubleshooting, and performance tuning for optimal inference on NVIDIA hardware. Changes
Sequence Diagram(s)Not applicable: No new feature or control flow logic was introduced in code; only documentation was added. Estimated code review effort🎯 2 (Simple) | ⏱️ ~6 minutes Suggested reviewers
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🧹 Nitpick comments (6)
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md (6)
11-12: Replace HTML break tags with native Markdown spacingUsing raw
<br>tags defeats Markdown portability, breaks some renderers, and triggers linter warnings.
Just leave a blank line (or two) between paragraphs instead of</br></br>.-</br></br> - + <!-- delete the tag entirely – keep the blank line -->Also applies to: 23-24, 44-45, 57-58, 136-137, 216-217
29-30: Grammar: “following” not “follow”-Run the follow docker command to start the TensorRT-LLM container in interactive mode: +Run the following Docker command to start the TensorRT-LLM container in interactive mode:
61-62: Grammar: plural agreement-Each requires a different configurations and commands to run. +Each scenario requires different configurations and commands to run.
86-88: Typo: “configures” → “configurations”-...Commands for different GPU configures are provided (1xGPU, 8xGPU, 4xGPU): +...Commands for different GPU configurations are provided (1×GPU, 8×GPU, 4×GPU):
229-229: MD019: remove double space after heading marker-## (Optional) Using the MXFP4 Checkpoints +## (Optional) Using the MXFP4 Checkpoints
242-242: Spelling: “contrainer” → “container”-OpenAI ships a set of Triton kernels optimized for its MoE models. TensorRT-LLM can leverage these kernels for Hopper based GPUs like NVIDIA's H200 to gain significant speed-ups. The NGC TensorRT-LLM contrainer image mentioned above already includes the required kernel so you do not need to build or install it. It is highly recommended to enable them with the steps below: +OpenAI ships a set of Triton kernels optimized for its MoE models. TensorRT-LLM can leverage these kernels for Hopper-based GPUs like NVIDIA's H200 to gain significant speed-ups. The NGC TensorRT-LLM container image mentioned above already includes the required kernel, so you do not need to build or install it. It is highly recommended to enable them with the steps below:
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🧠 Learnings (2)
📓 Common learnings
Learnt from: moraxu
PR: NVIDIA/TensorRT-LLM#6303
File: tests/integration/test_lists/qa/examples_test_list.txt:494-494
Timestamp: 2025-07-28T17:06:08.621Z
Learning: In TensorRT-LLM testing, it's common to have both CLI flow tests (test_cli_flow.py) and PyTorch API tests (test_llm_api_pytorch.py) for the same model. These serve different purposes: CLI flow tests validate the traditional command-line workflow, while PyTorch API tests validate the newer LLM API backend. Both are legitimate and should coexist.
Learnt from: yibinl-nvidia
PR: NVIDIA/TensorRT-LLM#6506
File: examples/models/core/mixtral/requirements.txt:3-3
Timestamp: 2025-08-01T15:14:45.673Z
Learning: In TensorRT-LLM, examples directory can have different dependency versions than the root requirements.txt file. Version conflicts between root and examples dependencies are acceptable because examples are designed to be standalone and self-contained.
📚 Learning: in tensorrt-llm testing, it's common to have both cli flow tests (test_cli_flow.py) and pytorch api ...
Learnt from: moraxu
PR: NVIDIA/TensorRT-LLM#6303
File: tests/integration/test_lists/qa/examples_test_list.txt:494-494
Timestamp: 2025-07-28T17:06:08.621Z
Learning: In TensorRT-LLM testing, it's common to have both CLI flow tests (test_cli_flow.py) and PyTorch API tests (test_llm_api_pytorch.py) for the same model. These serve different purposes: CLI flow tests validate the traditional command-line workflow, while PyTorch API tests validate the newer LLM API backend. Both are legitimate and should coexist.
Applied to files:
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
🪛 LanguageTool
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
[grammar] ~242-~242: Ensure spelling is correct
Context: ...ificant speed-ups. The NGC TensorRT-LLM contrainer image mentioned above already includes ...
(QB_NEW_EN_ORTHOGRAPHY_ERROR_IDS_1)
🪛 markdownlint-cli2 (0.17.2)
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
229-229: Multiple spaces after hash on atx style heading
(MD019, no-multiple-space-atx)
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🧹 Nitpick comments (4)
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md (4)
61-62: Grammar tweak for clarityThe phrase “requires a different configurations” mixes singular and plural.
Simplify to “requires different configurations” to avoid the grammatical stumble.-As pointed out in the introduction, this guide covers low-latency and max-throughput cases. Each requires a different configurations and commands to run. +As pointed out in the introduction, this guide covers low-latency and max-throughput cases. Each requires different configurations and commands to run.
69-79: Code-block language tag is misleadingThe block is declared as
yaml, but it actually contains a shell heredoc.
Marking it asbash(or splitting into separate shell + YAML examples) will give
correct syntax highlighting and reduce reader confusion.-```yaml -cat <<EOF > low_latency.yaml +```bash +cat <<EOF > low_latency.yaml enable_attention_dp: false ... EOFRepeat the same adjustment for the corresponding *max_throughput.yaml* snippet below (Lines 148-157). --- `148-157`: **Same language-tag issue as above** This snippet is also a shell heredoc, not pure YAML. Apply the same `bash` tag swap to maintain consistency and syntax highlighting. --- `229-229`: **Remove extra space after the heading marker (MD019)** Markdown-lint flags “multiple spaces after hash”. Trim the redundant space to keep headings well-formed. ```diff -## (Optional) Using the MXFP4 Checkpoints +## (Optional) Using the MXFP4 Checkpoints
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🧠 Learnings (3)
📓 Common learnings
Learnt from: moraxu
PR: NVIDIA/TensorRT-LLM#6303
File: tests/integration/test_lists/qa/examples_test_list.txt:494-494
Timestamp: 2025-07-28T17:06:08.621Z
Learning: In TensorRT-LLM testing, it's common to have both CLI flow tests (test_cli_flow.py) and PyTorch API tests (test_llm_api_pytorch.py) for the same model. These serve different purposes: CLI flow tests validate the traditional command-line workflow, while PyTorch API tests validate the newer LLM API backend. Both are legitimate and should coexist.
Learnt from: yibinl-nvidia
PR: NVIDIA/TensorRT-LLM#6506
File: examples/models/core/mixtral/requirements.txt:3-3
Timestamp: 2025-08-01T15:14:45.673Z
Learning: In TensorRT-LLM, examples directory can have different dependency versions than the root requirements.txt file. Version conflicts between root and examples dependencies are acceptable because examples are designed to be standalone and self-contained.
📚 Learning: in tensorrt-llm, examples directory can have different dependency versions than the root requirement...
Learnt from: yibinl-nvidia
PR: NVIDIA/TensorRT-LLM#6506
File: examples/models/core/mixtral/requirements.txt:3-3
Timestamp: 2025-08-01T15:14:45.673Z
Learning: In TensorRT-LLM, examples directory can have different dependency versions than the root requirements.txt file. Version conflicts between root and examples dependencies are acceptable because examples are designed to be standalone and self-contained.
Applied to files:
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
📚 Learning: in tensorrt-llm testing, it's common to have both cli flow tests (test_cli_flow.py) and pytorch api ...
Learnt from: moraxu
PR: NVIDIA/TensorRT-LLM#6303
File: tests/integration/test_lists/qa/examples_test_list.txt:494-494
Timestamp: 2025-07-28T17:06:08.621Z
Learning: In TensorRT-LLM testing, it's common to have both CLI flow tests (test_cli_flow.py) and PyTorch API tests (test_llm_api_pytorch.py) for the same model. These serve different purposes: CLI flow tests validate the traditional command-line workflow, while PyTorch API tests validate the newer LLM API backend. Both are legitimate and should coexist.
Applied to files:
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
🪛 markdownlint-cli2 (0.17.2)
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
229-229: Multiple spaces after hash on atx style heading
(MD019, no-multiple-space-atx)
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schetlur-nv
approved these changes
Aug 5, 2025
| - Sets up shared memory and stack limits for optimal performance | ||
| - Maps port 8000 from the container to your host | ||
| - enables PDL for low-latency perf optimization | ||
| - disables parallel weight loading |
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This section helps explain some of the docker run arguments for the users so vote we keep it in the guide.
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Not the whole section - I mean why do we need to disable parallel weight loading. For eg above you said that we need to enable PDL for low latency optimization.
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Actionable comments posted: 0
🧹 Nitpick comments (3)
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md (3)
11-13: Replace the non-standard</br>tagsThe file uses the closing break tag
</br>in several places.
</br>is not valid HTML; Markdown processors either ignore it or render it verbatim.
Use a blank line (preferred) or<br>if you really need an explicit break.-</br> +(or)
-</br> +<br>Also applies to: 23-24, 44-45, 57-58, 136-137, 217-218, 239-240, 259-260, 364-365, 374-375
229-229: Fix Markdown heading spacing (MD019)There are two spaces between the hash marks and the heading text:
-## (Optional) Using the MXFP4 Checkpoints +## (Optional) Using the MXFP4 CheckpointsThis resolves the markdown-lint warning and keeps heading formatting consistent.
242-244: Typo: “contrainer” → “container”-The NGC TensorRT-LLM contrainer image mentioned above already includes +The NGC TensorRT-LLM container image mentioned above already includes
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🧠 Learnings (8)
📓 Common learnings
Learnt from: moraxu
PR: NVIDIA/TensorRT-LLM#6303
File: tests/integration/test_lists/qa/examples_test_list.txt:494-494
Timestamp: 2025-07-28T17:06:08.621Z
Learning: In TensorRT-LLM testing, it's common to have both CLI flow tests (test_cli_flow.py) and PyTorch API tests (test_llm_api_pytorch.py) for the same model. These serve different purposes: CLI flow tests validate the traditional command-line workflow, while PyTorch API tests validate the newer LLM API backend. Both are legitimate and should coexist.
Learnt from: yibinl-nvidia
PR: NVIDIA/TensorRT-LLM#6506
File: examples/models/core/mixtral/requirements.txt:3-3
Timestamp: 2025-08-01T15:14:45.673Z
Learning: In TensorRT-LLM, examples directory can have different dependency versions than the root requirements.txt file. Version conflicts between root and examples dependencies are acceptable because examples are designed to be standalone and self-contained.
📚 Learning: in tensorrt-llm, examples directory can have different dependency versions than the root requirement...
Learnt from: yibinl-nvidia
PR: NVIDIA/TensorRT-LLM#6506
File: examples/models/core/mixtral/requirements.txt:3-3
Timestamp: 2025-08-01T15:14:45.673Z
Learning: In TensorRT-LLM, examples directory can have different dependency versions than the root requirements.txt file. Version conflicts between root and examples dependencies are acceptable because examples are designed to be standalone and self-contained.
Applied to files:
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
📚 Learning: in tensorrt-llm testing, it's common to have both cli flow tests (test_cli_flow.py) and pytorch api ...
Learnt from: moraxu
PR: NVIDIA/TensorRT-LLM#6303
File: tests/integration/test_lists/qa/examples_test_list.txt:494-494
Timestamp: 2025-07-28T17:06:08.621Z
Learning: In TensorRT-LLM testing, it's common to have both CLI flow tests (test_cli_flow.py) and PyTorch API tests (test_llm_api_pytorch.py) for the same model. These serve different purposes: CLI flow tests validate the traditional command-line workflow, while PyTorch API tests validate the newer LLM API backend. Both are legitimate and should coexist.
Applied to files:
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
📚 Learning: applies to **/*.py : the code developed for tensorrt-llm should conform to python 3.8+....
Learnt from: CR
PR: NVIDIA/TensorRT-LLM#0
File: CODING_GUIDELINES.md:0-0
Timestamp: 2025-08-05T07:49:09.875Z
Learning: Applies to **/*.py : The code developed for TensorRT-LLM should conform to Python 3.8+.
Applied to files:
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
📚 Learning: in tensorrt-llm's multimodal processing pipeline, shared tensor recovery using `from_shared_tensor()...
Learnt from: yechank-nvidia
PR: NVIDIA/TensorRT-LLM#6254
File: tensorrt_llm/_torch/pyexecutor/model_engine.py:1201-1204
Timestamp: 2025-07-22T09:22:14.726Z
Learning: In TensorRT-LLM's multimodal processing pipeline, shared tensor recovery using `from_shared_tensor()` is only needed during the context phase. Generation requests reuse the already-recovered tensor data and only need to call `strip_for_generation()` to remove unnecessary multimodal data while preserving the recovered tensors. This avoids redundant tensor recovery operations during generation.
Applied to files:
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
📚 Learning: in the tensorrt-llm waive list merging system, removed lines are always located at the end of the me...
Learnt from: yiqingy0
PR: NVIDIA/TensorRT-LLM#5198
File: jenkins/mergeWaiveList.py:0-0
Timestamp: 2025-07-22T08:33:49.109Z
Learning: In the TensorRT-LLM waive list merging system, removed lines are always located at the end of the merge waive lists, which is why the mergeWaiveList.py script uses reverse traversal - it's an optimization for this specific domain constraint.
Applied to files:
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
📚 Learning: applies to **/*.{h,hpp} : use a preprocessor guard in header files. the guard name must have prefix ...
Learnt from: CR
PR: NVIDIA/TensorRT-LLM#0
File: CODING_GUIDELINES.md:0-0
Timestamp: 2025-08-05T07:49:09.875Z
Learning: Applies to **/*.{h,hpp} : Use a preprocessor guard in header files. The guard name must have prefix TRTLLM_ followed by the filename, all in caps, and no trailing underscore.
Applied to files:
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
📚 Learning: applies to **/*.{cpp,h,cu,py} : all tensorrt-llm open source software code should contain an nvidia ...
Learnt from: CR
PR: NVIDIA/TensorRT-LLM#0
File: CODING_GUIDELINES.md:0-0
Timestamp: 2025-08-05T07:49:09.875Z
Learning: Applies to **/*.{cpp,h,cu,py} : All TensorRT-LLM Open Source Software code should contain an NVIDIA copyright header that includes the current year. This includes .cpp, .h, .cu, .py, and any other source files which are compiled or interpreted.
Applied to files:
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
🪛 LanguageTool
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
[grammar] ~242-~242: Ensure spelling is correct
Context: ...ificant speed-ups. The NGC TensorRT-LLM contrainer image mentioned above already includes ...
(QB_NEW_EN_ORTHOGRAPHY_ERROR_IDS_1)
🪛 markdownlint-cli2 (0.17.2)
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md
229-229: Multiple spaces after hash on atx style heading
(MD019, no-multiple-space-atx)
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🔇 Additional comments (1)
docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md (1)
88-101: Verifympirun -n 1for multi-GPU examplesAll three launch examples (1 GPU / 8 GPU / 4 GPU) use
mpirun -n 1.
If the intention is to run one process per GPU, the-nvalue should match the
GPU count (e.g.-n 8for the 8-GPU case).
Please double-check this before publishing.Also applies to: 104-117, 182-197, 199-213
Co-authored-by: Sharan Chetlur <116769508+schetlur-nv@users.noreply.github.com> Signed-off-by: Farshad Ghodsian <47931571+farshadghodsian@users.noreply.github.com>
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Summary by CodeRabbit
Description
Adding Deployment Guide documentation for GPT-OSS model.
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No code tests required as this is a documentation change only.
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