[None][test] add Nemotron Ultra V3 AutoDeploy accuracy test by tcherckez-nvidia · Pull Request #13658 · NVIDIA/TensorRT-LLM

tcherckez-nvidia · 2026-04-30T09:27:03Z

Summary by CodeRabbit

New Features
- Introduced Nemotron-Ultra-V3 model with optimized performance configurations for enhanced inference capabilities.
- Established accuracy benchmarks across standard evaluation datasets.
Tests
- Added comprehensive integration accuracy tests spanning multiple hardware configurations and inference backends.
- Implemented test coverage for both single and distributed multi-GPU deployment scenarios.

Description

Test Coverage

PR Checklist

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tcherckez-nvidia · 2026-04-30T09:28:04Z

/bot run --extra-stage "DGX_B200-4_GPUs-AutoDeploy-1, DGX_H100-4_GPUs-AutoDeploy-1"

coderabbitai · 2026-04-30T09:28:31Z

📝 Walkthrough

Walkthrough

This pull request adds support for the Nemotron-Ultra-V3 model by introducing model registry configuration, accuracy reference benchmarks for GSM8K and MMLU, an integration test class with parametrized testing across multiple backends and configurations, test list entries, and HuggingFace Hub ID mapping support.

Changes

Cohort / File(s)	Summary
Model Configuration `examples/auto_deploy/model_registry/configs/ultra_v3.yaml`	New model registry config for ultra_v3 with TensorRT-LLM runtime, CUDA graph compilation, chunked prefill, mamba attention backend, and compilation optimizations including MoE fusion, SSM attention caching, and sharding detection via SYMM_MEM allreduce strategy.
Accuracy References `tests/integration/defs/accuracy/references/gsm8k.yaml`, `tests/integration/defs/accuracy/references/mmlu.yaml`	New accuracy reference entries for nvidia/Nemotron-Ultra-V3 with NVFP4 quantization and FP8 KV-cache quantization, specifying GSM8K accuracy of 91.797 and MMLU accuracy of 85.70.
Integration Tests `tests/integration/defs/accuracy/test_llm_api_autodeploy.py`, `tests/integration/test_lists/test-db/l0_dgx_b200.yml`	New test class TestNemotronUltraV3 with parametrized accuracy tests across flashinfer and trtllm backends, attention-DP sharding modes, and multi-GPU world sizes (4, 8); corresponding test list entries added for l0_dgx_b200 configurations.
Data Mapping `tests/test_common/llm_data.py`	Added HuggingFace Hub ID mapping for nvidia/Nemotron-Ultra-V3-NVFP4 to local model directory resolution in mock_snapshot_download function.

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~12 minutes

🚥 Pre-merge checks | ✅ 3 | ❌ 2

❌ Failed checks (2 warnings)

Check name	Status	Explanation	Resolution
Description check	⚠️ Warning	The PR description is incomplete; it contains only the template structure with empty sections for Description and Test Coverage, and lacks actual implementation details.	Fill in the Description section explaining what test is being added and why, and the Test Coverage section listing the relevant test cases added (e.g., TestNemotronUltraV3 with MMLU/GSM8K accuracy tests).
Docstring Coverage	⚠️ Warning	Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (3 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly summarizes the main change: adding an AutoDeploy accuracy test for Nemotron Ultra V3 model.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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tensorrt-cicd · 2026-04-30T09:34:32Z

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Actionable comments posted: 1

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Some comments are outside the diff and can’t be posted inline due to platform limitations.

⚠️ Outside diff range comments (1)

tests/integration/test_lists/test-db/l0_dgx_b200.yml (1)

326-335: ⚠️ Potential issue | 🟠 Major | ⚡ Quick win

Add a pre-merge trtllm Ultra-V3 selection.

The new model-registry path is trtllm-oriented, but this pre-merge block only schedules the flashinfer variant. That leaves the primary runtime unvalidated until post-merge.

Suggested fix

   - accuracy/test_llm_api_autodeploy.py::TestNemotronUltraV3::test_accuracy[nvfp4-4-attn_dp_off-flashinfer]
+  - accuracy/test_llm_api_autodeploy.py::TestNemotronUltraV3::test_accuracy[nvfp4-4-attn_dp_off-trtllm]

🤖 Prompt for AI Agents

Verify each finding against the current code and only fix it if needed.

In `@tests/integration/test_lists/test-db/l0_dgx_b200.yml` around lines 326 - 335,
The pre-merge test list schedules only the flashinfer variant for Ultra-V3,
leaving the new trtllm-oriented model-registry path untested; update the
pre-merge block in this YAML to include a trtllm Ultra-V3 entry (mirror the
existing
accuracy/test_llm_api_autodeploy.py::TestNemotronUltraV3::test_accuracy[nvfp4-4-attn_dp_off-flashinfer]
line) so the corresponding trtllm runtime is validated pre-merge, and ensure any
grouping keys or tags used for pre-merge selection reference the trtllm variant
as well.

🤖 Prompt for all review comments with AI agents

Verify each finding against the current code and only fix it if needed.

Inline comments:
In `@tests/integration/defs/accuracy/test_llm_api_autodeploy.py`:
- Around line 722-785: The test exercises only the NVFP4 path
(MODEL_PATHS["nvfp4"]) so add an early guard in
TestNemotronUltraV3.test_accuracy to skip when the host GPUs are not
Blackwell/B200-class; specifically, after the existing get_device_count() check,
call the project helper that detects Blackwell/B200 GPUs (e.g., is_blackwell()
or the equivalent GPU-family detection helper) and pytest.skip with a
descriptive message if it returns False, ensuring the test only runs on
Blackwell systems.

---

Outside diff comments:
In `@tests/integration/test_lists/test-db/l0_dgx_b200.yml`:
- Around line 326-335: The pre-merge test list schedules only the flashinfer
variant for Ultra-V3, leaving the new trtllm-oriented model-registry path
untested; update the pre-merge block in this YAML to include a trtllm Ultra-V3
entry (mirror the existing
accuracy/test_llm_api_autodeploy.py::TestNemotronUltraV3::test_accuracy[nvfp4-4-attn_dp_off-flashinfer]
line) so the corresponding trtllm runtime is validated pre-merge, and ensure any
grouping keys or tags used for pre-merge selection reference the trtllm variant
as well.

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Create a new PR with the fixes

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📥 Commits

Reviewing files that changed from the base of the PR and between 24228e9 and 5f905e2.

📒 Files selected for processing (6)

examples/auto_deploy/model_registry/configs/ultra_v3.yaml
tests/integration/defs/accuracy/references/gsm8k.yaml
tests/integration/defs/accuracy/references/mmlu.yaml
tests/integration/defs/accuracy/test_llm_api_autodeploy.py
tests/integration/test_lists/test-db/l0_dgx_b200.yml
tests/test_common/llm_data.py

tensorrt-cicd · 2026-04-30T14:17:00Z

PR_Github #46356 [ run ] completed with state SUCCESS. Commit: 5f905e2
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tcherckez-nvidia · 2026-05-03T07:18:33Z

/bot run --extra-stage "DGX_B200-4_GPUs-AutoDeploy-1, DGX_H100-4_GPUs-AutoDeploy-1"

tensorrt-cicd · 2026-05-03T07:24:23Z

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tcherckez-nvidia · 2026-05-06T05:50:56Z

/bot run --extra-stage "DGX_B200-4_GPUs-AutoDeploy-1, DGX_H100-4_GPUs-AutoDeploy-1"

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tcherckez-nvidia · 2026-05-06T12:16:40Z

/bot run --extra-stage "DGX_B200-4_GPUs-AutoDeploy-1, DGX_H100-4_GPUs-AutoDeploy-1" --reuse-test

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tcherckez-nvidia · 2026-05-07T05:02:03Z

/bot run --extra-stage "DGX_B200-4_GPUs-AutoDeploy-1, DGX_H100-4_GPUs-AutoDeploy-1" --reuse-test

tensorrt-cicd · 2026-05-07T06:27:32Z

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tcherckez-nvidia · 2026-05-11T13:48:23Z

/bot run --extra-stage "DGX_B200-4_GPUs-AutoDeploy-1" --reuse-test

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Signed-off-by: Tal Cherckez <[email protected]>

tcherckez-nvidia · 2026-05-12T05:54:51Z

/bot run --extra-stage "DGX_B200-4_GPUs-AutoDeploy-1" --reuse-test

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tcherckez-nvidia · 2026-05-12T15:26:43Z

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tcherckez-nvidia · 2026-05-12T15:28:06Z

/bot run --stage-list "DGX_B200-4_GPUs-AutoDeploy-1"

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…3658) Signed-off-by: Tal Cherckez <[email protected]>

tcherckez-nvidia requested review from a team as code owners April 30, 2026 09:27

tcherckez-nvidia requested a review from bmarimuthu-nv April 30, 2026 09:27

tcherckez-nvidia force-pushed the ultra-v3-tests branch from bf4fba1 to 5f905e2 Compare April 30, 2026 09:27

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Comment thread tests/integration/defs/accuracy/test_llm_api_autodeploy.py

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tcherckez-nvidia force-pushed the ultra-v3-tests branch from 5f905e2 to eee2b19 Compare May 3, 2026 07:01

tcherckez-nvidia enabled auto-merge (squash) May 6, 2026 14:13

tcherckez-nvidia force-pushed the ultra-v3-tests branch from eee2b19 to 7f0b29f Compare May 7, 2026 06:16

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Comment thread tests/integration/test_lists/test-db/l0_dgx_b200.yml

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tcherckez-nvidia and others added 3 commits May 12, 2026 08:54

[None][test] add Nemotron Ultra V3 AutoDeploy accuracy test

0b3b193

Signed-off-by: Tal Cherckez <[email protected]>

remove flavors, skip test for pre blackwell

d62d456

Signed-off-by: Tal Cherckez <[email protected]>

fix: make FlashInfer Mamba decode inputs contiguous

312bdb8

Signed-off-by: Tal Cherckez <[email protected]>

tcherckez-nvidia force-pushed the ultra-v3-tests branch from a7d298a to 312bdb8 Compare May 12, 2026 05:54

tcherckez-nvidia merged commit 113bc64 into NVIDIA:main May 12, 2026
6 checks passed

yufeiwu-nv pushed a commit to yufeiwu-nv/TensorRT-LLM that referenced this pull request May 19, 2026

[None][test] add Nemotron Ultra V3 AutoDeploy accuracy test (NVIDIA#1…

b7beb44

…3658) Signed-off-by: Tal Cherckez <[email protected]>

This was referenced May 20, 2026

[#14173][tests] move autodeploy accuracy tests to post merge and use model registry #14352

Open

[None][perf] Add AutoDeploy NVFP4 RMSNorm quant fusion #14361

Open

[TRTLLM-12154][test] Add Qwen3-32B FP8 disagg stress test #14278

Open

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