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[ModelOpt] Support Qwen3.5/3.6 VLM quantized prefix mapping#42546

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pavanimajety merged 16 commits into
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May 23, 2026
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[ModelOpt] Support Qwen3.5/3.6 VLM quantized prefix mapping#42546
pavanimajety merged 16 commits into
vllm-project:mainfrom
meenchen:weimingc/qwen_vlm_modelopt_mapping

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@meenchen meenchen commented May 13, 2026

Purpose

Add Qwen3.5/3.6 VLM checkpoint prefix mapping for ModelOpt mixed-precision checkpoints.

Qwen VLM checkpoints can export language model tensors and quantization config entries with wrapper prefixes such
as model.language_model.* or language_model.model.*, while vLLM constructs the text model modules under
normalized internal prefixes such as model.* / lm_head.*.

This PR adds the required mapping so:

  • Qwen3.5/3.6 VLM checkpoint weights load into the expected vLLM module names.
  • ModelOpt quantized_layers entries resolve correctly when wrapper prefix ordering differs.
  • Nested VLM lm_head prefixes resolve to top-level lm_head quantization metadata when lm_head quantization support is present. (related PR: Add LM head quantization support for ModelOpt #42124)

Test Plan

  • Run smoke generation with a Qwen3.6 VLM ModelOpt mixed-precision checkpoint.
  • Verify ModelOpt quantized_layers resolves the expected quantized modules when checkpoint prefixes use
    model.language_model.* / language_model.model.*.
  • Verify text-only loading works with Qwen VLM architecture override and disabled multimodal inputs.

Test Result

Tested locally on the cluster as part of the Qwen3.6 ModelOpt checkpoint smoke flow. The checkpoint loads with the
VLM prefix mapping, resolves quantized layer metadata, and generates text successfully.


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  • The test plan, such as providing test command.
  • The test results, such as pasting the results comparison before and after, or e2e results
  • (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

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@mergify mergify Bot added the qwen Related to Qwen models label May 13, 2026
@meenchen meenchen changed the title Weimingc/qwen vlm modelopt mapping [ModelOpt] Support Qwen3.5/3.6 VLM quantized prefix mapping May 13, 2026
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Code Review

This pull request enables quantization for the language model head in Nemotron-H and Qwen 3.5 models. Key changes include updating the ModelOpt quantization framework to support ParallelLMHead, implementing reciprocal round-trip logic for NVFP4 W4A16 to ensure bit-identical results with other backends, and introducing a prefix mapping utility to resolve quantization configurations across different model naming conventions. The PR also adds unit tests for these features and fixes a weight loading issue for scalar scales. Review feedback identifies missing prefix mappings required for Qwen VLM checkpoints to correctly resolve quantization methods.

Comment thread vllm/model_executor/layers/quantization/modelopt.py
@meenchen meenchen force-pushed the weimingc/qwen_vlm_modelopt_mapping branch from 93318ab to 3a2a20f Compare May 13, 2026 18:51
@meenchen meenchen marked this pull request as ready for review May 13, 2026 20:05
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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.

@meenchen meenchen force-pushed the weimingc/qwen_vlm_modelopt_mapping branch from 3a2a20f to 9510af7 Compare May 14, 2026 20:59
@pavanimajety pavanimajety added the verified Run pre-commit for new contributors without triggering other tests label May 15, 2026
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@pavanimajety pavanimajety added the ready ONLY add when PR is ready to merge/full CI is needed label May 19, 2026
meenchen added 2 commits May 19, 2026 22:47
Signed-off-by: weimingc <17592131+meenchen@users.noreply.github.com>
Signed-off-by: weimingc <17592131+meenchen@users.noreply.github.com>
@meenchen meenchen force-pushed the weimingc/qwen_vlm_modelopt_mapping branch from 8fc9541 to 64cc777 Compare May 20, 2026 05:57
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Thanks for the PR!

@pavanimajety pavanimajety enabled auto-merge (squash) May 22, 2026 17:34
@pavanimajety pavanimajety merged commit 09a219c into vllm-project:main May 23, 2026
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ECMGit added a commit to ECMGit/vllm that referenced this pull request May 25, 2026
…dently of --moe-backend

`--moe-backend` is consumed by both the NVFP4 dispatcher
(`oracle/nvfp4.py:map_nvfp4_backend`) and the FP8 dispatcher
(`oracle/fp8.py:map_fp8_backend`). For FP4-only kernels -- e.g.
`flashinfer_b12x` registered in NVFP4 oracle by PR vllm-project#40082 -- the FP8
dispatcher has no corresponding backend, so on any mixed-precision
checkpoint (NVFP4 experts + FP8 experts in the same model)
`map_fp8_backend` raises at engine init:

  ValueError: moe_backend='flashinfer_b12x' is not supported for FP8 MoE.
    Expected one of ['triton', 'deep_gemm', 'cutlass',
                     'flashinfer_trtllm', 'flashinfer_cutlass',
                     'marlin', 'aiter'].

This blocks every mixed-precision checkpoint that pairs NVFP4 expert
layers with FP8 ones -- e.g. `nvidia/Qwen3.6-35B-A3B-2.06GB-per-token`
on DGX Spark (GB10 / sm_121a). Such checkpoints are the norm for the
2.06GB-per-token family.

Introduce `VLLM_FP8_MOE_BACKEND` so callers can route FP8 experts to a
different backend (e.g. `flashinfer_cutlass`) while keeping
`--moe-backend=flashinfer_b12x` for the NVFP4 majority. Unset behavior
is unchanged -- only callers that explicitly set the env var see the
new dispatch.

PR vllm-project#42546 ("Support Qwen3.5/3.6 VLM quantized prefix mapping") is
unrelated scope (only touches quantization/modelopt.py). There is no
other in-review PR proposing VLLM_FP8_MOE_BACKEND; this is a clean
net-new env knob.

Alternatives considered:
1. Extend b12x to handle FP8 experts -- not feasible; b12x is FP4-only
   by construction (class docstring: "Only NVFP4 (kNvfp4Static/
   kNvfp4Dynamic) quantization is supported").
2. Auto-fall-back inside map_fp8_backend -- opaque and surprising; an
   explicit env-var opt-in is safer until the FP4/FP8 split is
   formalized in --moe-backend.
3. Per-layer-class backend selection in the model card -- larger
   refactor; this env var is the minimal unblocker.

Tested on DGX Spark (GB10, sm_121a) with vllm/vllm-openai:nightly-aarch64
+ this PR + the b12x-W4A16-supports companion PR.
Model: nvidia/Qwen3.6-35B-A3B-2.06GB-per-token (modelopt-native,
mixed NVFP4 + FP8 experts).
Recipe:
  export VLLM_NVFP4_GEMM_BACKEND=flashinfer-b12x
  export VLLM_USE_FLASHINFER_MOE_FP4=1
  export VLLM_FP8_MOE_BACKEND=flashinfer_cutlass   # THIS PR
  vllm serve nvidia/Qwen3.6-35B-A3B-2.06GB-per-token \
      --moe-backend=flashinfer_b12x --quantization=modelopt ...

aiperf K=3 AL=3.12, BS=1, ISL=2048+32K prefix=34,831, OSL=1024,
60 measured + 10 warmup, 0 errors:
  Output Token Throughput        : 91.00 tok/s
  Output Token Throughput / user : 97.42 tok/s/user
  TTFT                           : 746.81 ms
  ITL                            : 10.27 ms
  MTP acceptance length          : 3.15 (target 3.12)

Without this change, serve dies at engine init with the ValueError
above before any throughput can be measured.

Signed-off-by: Junhao Shen <junshen@nvidia.com>
h1t35h pushed a commit to h1t35h/vllm that referenced this pull request May 26, 2026
…ject#42546)

Signed-off-by: weimingc <17592131+meenchen@users.noreply.github.com>
ECMGit added a commit to ECMGit/vllm that referenced this pull request May 26, 2026
…dently of --moe-backend

`--moe-backend` is consumed by both the NVFP4 dispatcher
(`oracle/nvfp4.py:map_nvfp4_backend`) and the FP8 dispatcher
(`oracle/fp8.py:map_fp8_backend`). For FP4-only kernels -- e.g.
`flashinfer_b12x` registered in NVFP4 oracle by PR vllm-project#40082 -- the FP8
dispatcher has no corresponding backend, so on any mixed-precision
checkpoint (NVFP4 experts + FP8 experts in the same model)
`map_fp8_backend` raises at engine init:

  ValueError: moe_backend='flashinfer_b12x' is not supported for FP8 MoE.
    Expected one of ['triton', 'deep_gemm', 'cutlass',
                     'flashinfer_trtllm', 'flashinfer_cutlass',
                     'marlin', 'aiter'].

This blocks every mixed-precision checkpoint that pairs NVFP4 expert
layers with FP8 ones -- e.g. `nvidia/Qwen3.6-35B-A3B-2.06GB-per-token`
on DGX Spark (GB10 / sm_121a). Such checkpoints are the norm for the
2.06GB-per-token family.

Introduce `VLLM_FP8_MOE_BACKEND` so callers can route FP8 experts to a
different backend (e.g. `flashinfer_cutlass`) while keeping
`--moe-backend=flashinfer_b12x` for the NVFP4 majority. Unset behavior
is unchanged -- only callers that explicitly set the env var see the
new dispatch.

PR vllm-project#42546 ("Support Qwen3.5/3.6 VLM quantized prefix mapping") is
unrelated scope (only touches quantization/modelopt.py). There is no
other in-review PR proposing VLLM_FP8_MOE_BACKEND; this is a clean
net-new env knob.

Alternatives considered:
1. Extend b12x to handle FP8 experts -- not feasible; b12x is FP4-only
   by construction (class docstring: "Only NVFP4 (kNvfp4Static/
   kNvfp4Dynamic) quantization is supported").
2. Auto-fall-back inside map_fp8_backend -- opaque and surprising; an
   explicit env-var opt-in is safer until the FP4/FP8 split is
   formalized in --moe-backend.
3. Per-layer-class backend selection in the model card -- larger
   refactor; this env var is the minimal unblocker.

Tested on DGX Spark (GB10, sm_121a) with vllm/vllm-openai:nightly-aarch64
+ this PR + the b12x-W4A16-supports companion PR.
Model: nvidia/Qwen3.6-35B-A3B-2.06GB-per-token (modelopt-native,
mixed NVFP4 + FP8 experts).
Recipe:
  export VLLM_NVFP4_GEMM_BACKEND=flashinfer-b12x
  export VLLM_USE_FLASHINFER_MOE_FP4=1
  export VLLM_FP8_MOE_BACKEND=flashinfer_cutlass   # THIS PR
  vllm serve nvidia/Qwen3.6-35B-A3B-2.06GB-per-token \
      --moe-backend=flashinfer_b12x --quantization=modelopt ...

aiperf K=3 AL=3.12, BS=1, ISL=2048+32K prefix=34,831, OSL=1024,
60 measured + 10 warmup, 0 errors:
  Output Token Throughput        : 91.00 tok/s
  Output Token Throughput / user : 97.42 tok/s/user
  TTFT                           : 746.81 ms
  ITL                            : 10.27 ms
  MTP acceptance length          : 3.15 (target 3.12)

Without this change, serve dies at engine init with the ValueError
above before any throughput can be measured.

Signed-off-by: Junhao Shen <junshen@nvidia.com>
Liuweixiong0118 pushed a commit to Liuweixiong0118/vllm that referenced this pull request Jun 1, 2026
…ject#42546)

Signed-off-by: weimingc <17592131+meenchen@users.noreply.github.com>
Signed-off-by: Liuweixiong0118 <lwx34158427@gmail.com>
amd-callumm added a commit to ROCm/vllm that referenced this pull request Jun 2, 2026
* [XPU] add gptq(int4) support (#37844)

Signed-off-by: Kunshang Ji <kunshang.ji@intel.com>

* [UX] Add a persistent cache for FlashInfer autotuning (#42537)

Signed-off-by: Mohammad Miadh Angkad <176301910+mmangkad@users.noreply.github.com>

* [Bugfix][MRV2] Fix KVCache tensor explicit `kernel_block_size` dim (#42766)

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Signed-off-by: Nick Hill <nickhill123@gmail.com>
Co-authored-by: Nick Hill <nickhill123@gmail.com>

* [Model Refactoring] Move DeepSeek V4 layers to `models/deepseek_v4/` [2/N] (#43039)

Signed-off-by: Woosuk Kwon <woosuk@inferact.ai>

* add cutedsl dsv4 indexer fp8 kernel (#42899)

Signed-off-by: george <george@inferact.ai>
Co-authored-by: george <george@inferact.ai>

* [Bugfix][KV Connector] Fix SimpleCPUOffloadScheduler TOCTOU between Phase A and Phase B (#42289)

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* [ci] Route 28 gpu_1_queue tests to h200_35gb queue (#43030)

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix: use keyword arguments for shard_id and expert_id in weight_loade… (#42671)

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* [Docs] Add SVG images for pooling models. (#42626)

Signed-off-by: Gracie Guo <gracieguo@Gracies-MacBook-Pro.local>
Signed-off-by: wang.yuqi <yuqi.wang@daocloud.io>
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Co-authored-by: wang.yuqi <yuqi.wang@daocloud.io>

* [XPU] Use custom op collective behavior  (#41354)

Signed-off-by: Chaojun,Zhang <chaojun.zhang@intel.com>
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* [Misc] Aligning tokwise pooler heads for consistency (#43041)

Signed-off-by: Taneem Ibrahim <taneem.ibrahim@gmail.com>

* [Docs] Reorganize online serving docs. (#41907)

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Signed-off-by: wang.yuqi <noooop@126.com>
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* [Frontend] Consolidate beam search by BeamSearchMixin. (#42946)

Signed-off-by: wang.yuqi <yuqi.wang@daocloud.io>

* [Model Refactoring] Move deepseek_v4_ops to models/deepseek_v4 [3/N] (#43073)

Signed-off-by: Woosuk Kwon <woosuk@inferact.ai>

* [bug] AsyncScheduler drops first post-resume token after pause_generation + clear_cache (#42117)

Signed-off-by: hao-aaron <ahao@anyscale.com>
Co-authored-by: mergify[bot] <37929162+mergify[bot]@users.noreply.github.com>

* [KVConnector][DSV4] HMA support for Mooncake store connector (#42828)

Signed-off-by: Yifan Qiao <yifanqiao@inferact.ai>

* [Model Refactoring] Rename deepseek_v4.py to model.py [4/N] (#43077)

Signed-off-by: Woosuk Kwon <woosuk@inferact.ai>

* [Misc][MM] Remove redundant code in CLIPAttention (#43046)

Signed-off-by: shen-shanshan <467638484@qq.com>

* [CI] Add MTP + PD disagg test for Qwen3.5 (#42677)

Signed-off-by: ZhanqiuHu <zhu@redhat.com>
Co-authored-by: Nicolò Lucchesi <nlucches@redhat.com>

* [Bugfix] Fix top logprobs token placeholders in `/inference/v1/generate` (#42887)

Signed-off-by: Sage Ahrac <sagiahrak@gmail.com>

* [Perf][4/n] Eliminate various GPU<->CPU syncs (#42347)

Signed-off-by: Nick Hill <nickhill123@gmail.com>

* [XPU] update xpu graph usage (#43043)

Signed-off-by: Xinyu Chen <xinyu1.chen@intel.com>

* [Model] Openvla support (#42654)

Signed-off-by: Wang Yiwen <121547057+yiwen101@users.noreply.github.com>

* [Refactor] Extract extract_types_from_schema utility from Minimax M2 tool parser (#43025)

Signed-off-by: sfeng33 <4florafeng@gmail.com>

* [Misc] add humming to dependencies (#42540)

Signed-off-by: Jinzhen Lin <jinzhen.ljz@antgroup.com>

* [feat] Add FP8 per-tensor Q scale support to Triton attention backend (#42080)

Signed-off-by: Dom Brown <3886319+DomBrown@users.noreply.github.com>

* [Docs] Fix MooncakeStoreConnector role in disaggregated example (#42994)

Signed-off-by: Dao Le <Dao007forever@gmail.com>
Co-authored-by: Claude <noreply@anthropic.com>

* [Bugfix][MoE] FlashInfer one-sided: workspace union across heterogeneous layers (#42976)

Signed-off-by: Tomer Asida <57313761+tomeras91@users.noreply.github.com>

* [CI failure] Temporarily disable using persistent cache for flashinfer autotune (#43119)

Signed-off-by: wzhao18 <wzhao18.sz@gmail.com>
Signed-off-by: Wei Zhao <51183510+wzhao18@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

* [ci] Move language models tests (hybrid) back to L4 (#43129)

Signed-off-by: Kevin H. Luu <khluu000@gmail.com>

* [Model] Support post-norm architecture for EAGLE-3 supeculators (#42764)

Signed-off-by: Doğaç Eldenk <dogacel@gmail.com>

* Fix error in Dynamic NTK scaling (#41277)

Signed-off-by: Max de Bayser <mbayser@br.ibm.com>
Signed-off-by: Max de Bayser <maxdebayser@gmail.com>
Signed-off-by: wang.yuqi <yuqi.wang@daocloud.io>
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* [CPU][DOC] Fix installation commands for Arm CPUs (#43115)

Signed-off-by: Fadi Arafeh <fadi.arafeh@arm.com>

* [bug] fix WeightTransferConfig.backend to allow for all strings (#43121)

Signed-off-by: ahao-anyscale <ahao@anyscale.com>

* [MRV2][BugFix] Fix default-stream CG capture in P/W LoRA case (#43160)

Signed-off-by: Nick Hill <nickhill123@gmail.com>

* [Cohere] Enable Cohere MoE (#43143)

Signed-off-by: Terrencezzj <terrence@cohere.ai>

* [Perf][Bugfix] Update dflash aux layer indexing (#40727)

Signed-off-by: Benjamin Chislett <bchislett@nvidia.com>

* add enqueue all option to throughput benchmark (#42975)

Signed-off-by: Philip Maybank <pmaybank@amd.com>
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* [Perf] Avoid forward scan for async output placeholders (#42938)

* [CI] Add DSV4-Flash to gsm8k moe-refactor/config-b200.txt (#42111)

Signed-off-by: mgoin <mgoin64@gmail.com>

* [KV Offload] Pass `OffloadingSpec` instead of `VllmConfig` to secondary tiers (#43076)

Signed-off-by: Ronen Schaffer <ronen.schaffer@ibm.com>

* [ci] Revert model executor test back to L4 (#43188)

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* [Docs][PD][NIXL] Lease extension mechanism for blocks on P (#43099)

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* [Docs][PD][NIXL] Bidirectional kv-cache transfer (#43097)

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* [6/n] Migrate activation kernels, gptq, gguf, non cutlass w8a8 to libtorch stable ABI (continued) (#42663)

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Signed-off-by: Chris Leonard <chleonar@redhat.com>
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* Enable mermaid diagrams in the docs (#43192)

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* [GDN] Enable FI Blackwell GDN prefill kernel (#40717)

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* [XPU][CI] Add 2 server model test files in Intel GPU CI (#42499)

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* [Frontend] Forward X-data-parallel-rank header on /inference/v1/generate (#42330)

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* [Doc] Sync CLI guide with actual help modes and launch subcommand (#40326)

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* [Feature] Support manually enabling the cumem allocator (#33648)

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* [Spec Decode] Support non-MTP speculation for NemotronH (#43130)

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* Remove additional dead code as a follow-up to #42889 (#43144)

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* [Bug][Structured Outputs] Fix bug that leads to unconstrained generations with structural tags (#42452)

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* [Bugfix] Use enable_sm120_family for per-tensor FP8 CUTLASS kernels on SM12.1 (#41215)

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Please see https://github.com/Inferact/vllm-frontend-rs for full original commit history.

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mvanhorn pushed a commit to mvanhorn/vllm that referenced this pull request Jun 4, 2026
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andakai pushed a commit to andakai/vllm that referenced this pull request Jun 4, 2026
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