---
id: pr-vllm-30484
repo: vllm-project/vllm
pr: 30484
title: '[Feature] Add SM103 (Blackwell Ultra) Support to vLLM'
author: LopezCastroRoberto
date: '2025-12-13'
url: https://github.com/vllm-project/vllm/pull/30484
source_category: upstream-code
architectures:
- sm100
tags:
- attention
- decode
- fp4
- fp8
- gemm
- kernel-fusion
- mla
- moe
- quantization
techniques:
- kernel-fusion
hardware_features:
- fp4
- fp8
kernel_types:
- attention
- decode
- gemm
- mla
- moe
- quantization
languages:
- cuda-cpp
captured_at: '2026-04-27'
status: merged
merge_sha: 4fa7ce46f31cbd97b4651694caf9991cc395a259
inclusion_reason: kernel file changes
changed_paths:
- tests/compile/distributed/test_fusions_e2e.py
- tests/kernels/attention/test_cutlass_mla_decode.py
- tests/kernels/attention/test_flashinfer_trtllm_attention.py
- tests/kernels/moe/test_ocp_mx_moe.py
- tests/quantization/test_blackwell_moe.py
- vllm/model_executor/layers/batch_invariant.py
- vllm/model_executor/layers/fused_moe/batched_deep_gemm_moe.py
- vllm/model_executor/layers/quantization/fp8.py
- vllm/model_executor/layers/quantization/mxfp4.py
- vllm/model_executor/layers/quantization/utils/flashinfer_fp4_moe.py
- vllm/model_executor/layers/quantization/utils/flashinfer_utils.py
- vllm/model_executor/layers/quantization/utils/fp8_utils.py
- vllm/model_executor/layers/quantization/utils/mxfp4_utils.py
- vllm/model_executor/models/config.py
- vllm/platforms/cuda.py
- vllm/platforms/interface.py
- vllm/utils/deep_gemm.py
- vllm/utils/flashinfer.py
- vllm/v1/attention/backends/flashinfer.py
- vllm/v1/attention/backends/mla/common.py
- vllm/v1/attention/backends/mla/flashmla_sparse.py
head_ref_oid: 68227a342968ea99ec8e678112d32adcd923cefa
artifact_dir: evidence/pull-bundles/vllm/gh-30484
---
# [Feature] Add SM103 (Blackwell Ultra) Support to vLLM

- Repository: `vllm-project/vllm`
- PR: [30484](https://github.com/vllm-project/vllm/pull/30484)
- Decision: `kernel file changes`
- Reason: kernel file changes

## Changed Paths

- `tests/compile/distributed/test_fusions_e2e.py`
- `tests/kernels/attention/test_cutlass_mla_decode.py`
- `tests/kernels/attention/test_flashinfer_trtllm_attention.py`
- `tests/kernels/moe/test_ocp_mx_moe.py`
- `tests/quantization/test_blackwell_moe.py`
- `vllm/model_executor/layers/batch_invariant.py`
- `vllm/model_executor/layers/fused_moe/batched_deep_gemm_moe.py`
- `vllm/model_executor/layers/quantization/fp8.py`
- `vllm/model_executor/layers/quantization/mxfp4.py`
- `vllm/model_executor/layers/quantization/utils/flashinfer_fp4_moe.py`
- `vllm/model_executor/layers/quantization/utils/flashinfer_utils.py`
- `vllm/model_executor/layers/quantization/utils/fp8_utils.py`
- `vllm/model_executor/layers/quantization/utils/mxfp4_utils.py`
- `vllm/model_executor/models/config.py`
- `vllm/platforms/cuda.py`
- `vllm/platforms/interface.py`
- `vllm/utils/deep_gemm.py`
- `vllm/utils/flashinfer.py`
- `vllm/v1/attention/backends/flashinfer.py`
- `vllm/v1/attention/backends/mla/common.py`
- `vllm/v1/attention/backends/mla/flashmla_sparse.py`

## Evidence Bundle

`evidence/pull-bundles/vllm/gh-30484`
