[CI/Build] chore(deps): bump flashinfer to v0.6.11

[AethoceSora]

Purpose

This PR bumps FlashInfer from the previous version to v0.6.11.
This PR may help integrate the FlashInfer B12x MoE and FP4 GEMM kernels for SM120/121. #40082

Test Plan

1. After upgrading the FlashInfer version, validate the changes through the existing CI pipeline to ensure all checks pass successfully (CI tag required).

2. Verify that, on SM120/SM121 devices, the FlashInfer b12x backend passes all unit tests (enabled via PR Integrate flashinfer b12x MoE and FP4 GEMM kernels for SM120/121 #40082).

3. Conduct end-to-end inference testing on SM120/SM121 devices using the FlashInfer b12x backend, and evaluate whether any performance or accuracy regressions are introduced.

Test Result

1. Based on the CI results, the new version of FlashInfer appears to be compatible with the existing workflow and does not introduce any regressions. There are currently three CI check failures, but they are not related to the changes introduced in this PR.
2. After applying fix(sm12x): fix micro-kernel workspace sizing when routed_rows > num_local_experts from FlashInfer, all B12x unit tests pass successfully on both RTX 5090 (SM120) and GB10 (SM121).
3. Test result1 Test result2

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• [✅] The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• [✅] The test plan, such as providing test command.
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[claude]

Claude Code Review

This pull request is from a fork — automated review is disabled. A repository maintainer can comment @claude review to run a one-time review.

[gemini-code-assist]

Code Review

This pull request updates FlashInfer to version 0.6.9 across the Docker configuration and requirements files. A potential issue was identified in the Dockerfile where the removal of the -dev suffix from libcublas could lead to runtime JIT compilation failures due to missing headers.

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[pavanimajety]

@AethoceSora, we need to update flashinfer to 0.6.9+ that includes cutlass fix for spark

[pavanimajety]

Please update to Flashinfer version that has flashinfer-jit-cache built with cutlass 4.5

[AethoceSora]

Please update to Flashinfer version that has flashinfer-jit-cache built with cutlass 4.5

Thanks for the clarification.

As I understand it, we need to wait for the CUTLASS fix to be merged and released as a new wheel (likely in a stable release such as 4.5.0). Then FlashInfer needs to update its nvidia-cutlass-dsl dependency to that version. After that, we can bump FlashInfer accordingly.

Please let me know if this understanding is correct.

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Note: Currently, flashinfer-jit-cache is not part of the build dependencies in vLLM.

I would appreciate your clarification on whether you were referring to nvidia-cutlass-dsl, or if you are suggesting that flashinfer-jit-cache be included as a build dependency for vLLM.

[AethoceSora]

Update:

Based on the CI results, the new version of FlashInfer appears to be compatible with the existing workflow and does not introduce any regressions.

There are currently three CI check failures, which have been confirmed to be unrelated to this PR.

[AethoceSora]

Update for the latest commit:

The new commit addresses the nvidia-cutlass-dsl issue where incorrect MMA ptxas files could be generated.

The fix selects the appropriate FlashInfer dependency based on the CUDA environment used to build vLLM:

• CUDA 12 builds use flashinfer-python
• CUDA 13 builds use flashinfer-python[cu13]

This allows FlashInfer to pull in the correct nvidia-cutlass-dsl variant transitively, instead of accidentally mixing incompatible CUTLASS DSL library variants.

More background is available here:

• Integrate flashinfer b12x MoE and FP4 GEMM kernels for SM120/121 #40082 (comment)
• [CuTe DSL] libs-base and libs-cu13 4.4.x ship divergent _cutlass_ir.so for the same path; libs-base emits malformed _mma PTX for SM120 mxf4nvf4 mma NVIDIA/cutlass#3170

[AethoceSora]

Please update to Flashinfer version that has flashinfer-jit-cache built with cutlass 4.5

I believe all prerequisites are now in place for merging both PR #40998 ([CI/Build] chore(deps): bump flashinfer to v0.6.11) and PR #40082 (Integrate flashinfer b12x MoE and FP4 GEMM kernels for SM120/121).

The relevant dependency and compatibility blockers have been resolved:

• nvidia-cutlass-dsl 4.5.0 stable has been released, which fixes the issue where sm_121a devices could not use MmaSM120BlockScaledOp.
• FlashInfer v0.6.11 has been released with nvidia-cutlass-dsl 4.5.0 as its dependency.
• Several issues that affected the use of the b12x backend on SM12x devices have been fixed and included in FlashInfer v0.6.11.

Relevant FlashInfer fixes:

• Cutlass dsl 4.5 bump flashinfer-ai/flashinfer#3246
• fix(sm12x): fix micro-kernel workspace sizing when routed_rows > num_local_experts flashinfer-ai/flashinfer#3191

Relevant Cutlass fixes:

• NVIDIA/cutlass@cb37157#diff-353c270c8ced4d47cd9fd493beca9ce6f72e3161fa00aa2894c1b07794bc881aR227

Given the above, the dependency stack should now be ready for enabling the FlashInfer b12x MoE and FP4 GEMM kernels for SM120/121 in vLLM.

Could you please review and merge this PR when you get a chance? Thanks!
cc @pavanimajety