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[TRTLLM-12500][feat] Add support for Qwen3.5 VL MoE (with the MTP fixes) - #14599

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2ez4bz merged 10 commits into
NVIDIA:mainfrom
moraxu:dev-mguzek-qwen3_5-moe-vl-v2
Jul 4, 2026
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[TRTLLM-12500][feat] Add support for Qwen3.5 VL MoE (with the MTP fixes)#14599
2ez4bz merged 10 commits into
NVIDIA:mainfrom
moraxu:dev-mguzek-qwen3_5-moe-vl-v2

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@moraxu moraxu commented May 26, 2026

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Summary by CodeRabbit

Release Notes

  • New Features

    • Added support for Qwen3.5 Mixture-of-Experts multimodal vision-language model (Qwen3.5-35B-A3B).
    • Extended speculative decoding to support vision-language model workflows.
    • Added FP8 block-scales quantization support for the new model.
  • Documentation

    • Updated feature support matrix to include Qwen3.5-MoE multimodal model capabilities.
  • Tests

    • Added accuracy validation tests for Qwen3.5-MoE multimodal model on standard benchmarks.
    • Added configuration and forward-parity verification tests.

Description

  • Completes Qwen3.5-MoE-VL (Qwen3_5MoeForConditionalGeneration) on top of #12611.
  • Switches the VLM config path to HF's native transformers.Qwen3_5MoeConfig (present in 5.3.0), adds a thin post-load normalizer that materializes the handful of aliases the reused Qwen3Next runtime expects on text_config (intermediate_size from the MoE fields, rope_theta/partial_rotary_factor/rope_scaling from rope_parameters), and centralizes hybrid-cache dtype resolution in two helpers.
  • 284291a: Makes Qwen3VLModelBase MTP/eagle-compatible: threads spec_metadata / resource_manager / pre-fusion orig_input_ids to the inner LM. Unblocks TestQwen3_5_35B_A3B::test_bf16_mtp[mtp_on], which started failing after [TRTLLM-11547][feat] Add Qwen3.5 MTP support. #12646 added the MTP test on top of the original [TRTLLM-12500][feat] Add support for Qwen3.5 VL MoE - REVERTED by #14599 #14164 and the same Qwen3.5-35B-A3B checkpoint started routing through the VLM wrapper - see nvbugs/6206179 for details
  • Commits specific to this PR follow after the first two commits

Test Coverage

Accuracy & unit tests

PR Checklist

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  • CODEOWNERS updated if ownership changes

  • Documentation updated as needed

  • Update tava architecture diagram if there is a significant design change in PR.

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  • Please check this after reviewing the above items as appropriate for this PR.

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2ez4bz merged commit 21260bb into NVIDIA:main Jul 4, 2026
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nv-guomingz added a commit to nv-guomingz/TensorRT-LLM that referenced this pull request Jul 7, 2026
…mba_ssm_cache_dtype is auto

PR NVIDIA#14599 made the 'auto' resolution of mamba_ssm_cache_dtype also honor
the checkpoint's mamba_ssm_dtype field. Qwen3.5 checkpoints declare
mamba_ssm_dtype=float32 (SSM compute intent), so the GDN state cache
silently flipped from bf16 to fp32. An fp32 state cache disables the
FlashInfer bf16-state GDN decode kernel (falls back to the slower Triton
recurrent kernel) and doubles state memory traffic and footprint,
regressing qwen3_5_397b_fp4_dep4_1k1k perf-sanity output throughput by
~19.5% (25435.9 -> 20479.4 tok/s) on B200.

Restore the pre-NVIDIA#14599 behavior: 'auto' resolves from the explicit
mamba_ssm_cache_dtype field (top-level or text_config) and otherwise
falls back to the model weights dtype. The checkpoint's mamba_ssm_dtype
is no longer used for cache allocation; users can still opt in
explicitly via kv_cache_config.mamba_ssm_cache_dtype.

Signed-off-by: nv-guomingz <137257613+nv-guomingz@users.noreply.github.com>
nv-guomingz added a commit to nv-guomingz/TensorRT-LLM that referenced this pull request Jul 7, 2026
…mba_ssm_cache_dtype is auto

PR NVIDIA#14599 made the 'auto' resolution of mamba_ssm_cache_dtype also honor
the checkpoint's mamba_ssm_dtype field. Qwen3.5 checkpoints declare
mamba_ssm_dtype=float32 (SSM compute intent), so the GDN state cache
silently flipped from bf16 to fp32. An fp32 state cache disables the
FlashInfer bf16-state GDN decode kernel (falls back to the slower Triton
recurrent kernel) and doubles state memory traffic and footprint,
regressing qwen3_5_397b_fp4_dep4_1k1k perf-sanity output throughput by
~19.5% (25435.9 -> 20479.4 tok/s) on B200.

Restore the pre-NVIDIA#14599 behavior: 'auto' resolves from the explicit
mamba_ssm_cache_dtype field (top-level or text_config) and otherwise
falls back to the model weights dtype. The checkpoint's mamba_ssm_dtype
is no longer used for cache allocation; users can still opt in
explicitly via kv_cache_config.mamba_ssm_cache_dtype.

Signed-off-by: nv-guomingz <137257613+nv-guomingz@users.noreply.github.com>
nv-guomingz added a commit to nv-guomingz/TensorRT-LLM that referenced this pull request Jul 7, 2026
…mba_ssm_cache_dtype is auto

PR NVIDIA#14599 made the 'auto' resolution of mamba_ssm_cache_dtype also honor
the checkpoint's mamba_ssm_dtype field. Qwen3.5 checkpoints declare
mamba_ssm_dtype=float32 (SSM compute intent), so the GDN state cache
silently flipped from bf16 to fp32. An fp32 state cache disables the
FlashInfer bf16-state GDN decode kernel (falls back to the slower Triton
recurrent kernel) and doubles state memory traffic and footprint,
regressing qwen3_5_397b_fp4_dep4_1k1k perf-sanity output throughput by
~19.5% (25435.9 -> 20479.4 tok/s) on B200.

Restore the pre-NVIDIA#14599 behavior: 'auto' resolves from the explicit
mamba_ssm_cache_dtype field (top-level or text_config) and otherwise
falls back to the model weights dtype. The checkpoint's mamba_ssm_dtype
is no longer used for cache allocation; users can still opt in
explicitly via kv_cache_config.mamba_ssm_cache_dtype.

Signed-off-by: nv-guomingz <137257613+nv-guomingz@users.noreply.github.com>
BrianLi23 pushed a commit to BrianLi23/TensorRT-LLM that referenced this pull request Jul 9, 2026
…es) (NVIDIA#14599)

Signed-off-by: Michal Guzek <mguzek@nvidia.com>
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