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[Bugfix] Add explicit error when using CFGP with distilled Cosmos3 models - #7427

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MaciejBalaNV:mbala/cosmos3_qol
Sep 11, 2026
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This PR adds explicit error when CFGP is used with distilled Cosmos3 models.

Purpose

This PR adds explicit error when CFGP is used with distilled Cosmos3 models. These models use guidance=1, so CFGP does not make sense or bring any benefit. Before this PR, CFGP was silently ignored and users would have pointlessly duplicated instances without any performance gain. After this PR an explicit error is thrown before the model is loaded so that we do not spend time on unnecessary model loading.

Test Plan

Unit tests

We add 8 new unit tests that verify whether the error is indeed thrown and whether other cases work fine.

Serving test

This command is now expected to fail with an appropriate error message: vllm serve nvidia/Cosmos3-Super-Image2Video-4Step --omni --cfg-parallel-size 2

vLLM Version:
0.29
vLLM-Omni Commit:
ToT

Test Result

Unit tests

All new unit tests pass

Serving tests

vllm serve nvidia/Cosmos3-Super-Image2Video-4Step --omni --cfg-parallel-size 2 indeed fails with ValueError: Distilled Cosmos3 checkpoints run without classifier-free guidance. Set --cfg-parallel-size 1 and use --ulysses-degree for multi-GPU inference. error message. vllm serve nvidia/Cosmos3-Super-Image2Video-4Step --omni --ulysses-degree 2 works fine and provides the expected speedup.

BEFORE SUBMITTING: read CONTRIBUTING.md and run the precheck-pr skill with the code agent for a self-check against project conventions.
(anything written below this line will be removed by GitHub Actions)

Signed-off-by: Maciej Bala <mbala@nvidia.com>
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📝 Code Review ✅ Completed 2026-09-11T12:20:12.388331Z 7b563ae PR opened
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This PR appears to belong to: docs/design/module/diffusion/offloader.md, docs/design/module/diffusion/diffusion_model_integration.md, docs/design/module/diffusion/index.md.

Module owners: @fhfuih @Bounty-hunter @david6666666

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@MaciejBalaNV, please review your own changes and leave a short self-review comment describing what you checked. PRs without author self-review may not be assigned a reviewer.

Please take a look when you have a chance. If you would like an automated review, mention @vllm-omni-review-bot in a comment.

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Overall this is a simple change that adds one ValueError after a check and moves scheduler initialization before the checkpoint loading.

Comment on lines +951 to +964
# Validate guidance parallelism from checkpoint metadata before loading
# components. Distilled checkpoints have only a conditional branch.
scheduler_config = FlowUniPCMultistepScheduler.load_config(
model_path,
subfolder="scheduler",
local_files_only=local_files_only,
)
self.is_distilled_model = scheduler_config.get("_class_name") == COSMOS3_DISTILLED_CHECKPOINT_SCHEDULER_CLASS
if self.is_distilled_model and od_config.parallel_config.cfg_parallel_size > 1:
raise ValueError(
"Distilled Cosmos3 checkpoints run without classifier-free guidance. "
"Set --cfg-parallel-size 1 and use --ulysses-degree for multi-GPU inference."
)

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The main part of the change is just moving the scheduler init here and adding the ValueError.

@hsliuustc0106 hsliuustc0106 added high priority high priority issue, needs to be done asap bug Something isn't working diffusion codes related to diffusion models labels Sep 11, 2026

@hsliuustc0106 hsliuustc0106 left a comment

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LGTM. Verified the fail-fast path end to end: the offload component-selector guard precedes the new scheduler-config read, so the error lands before any component load; the parallel_config deref is safe on all construction paths (dataclass default_factory + post-init normalization); and the guidance warning covers every distilled-reachable request path — non-T2I/T2V modes are hard-rejected and T2I/T2V/I2V route through _resolve_guidance_scale. The new tests fail on base and exercise the real load_config, so they pin both behaviors.

One note: no CI lane has run the new unit tests on this head — the green evidence is author-run only. Consider adding a trigger label if you want lane coverage before merge.

@lishunyang12

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Can you briefly introduce what is CFGP? sorry that my context does not cover this model recently,

@MaciejBalaNV

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@lishunyang12
It's --cfg-parallel-size option in vllm serve which parallelizes the model across the classifier-free guidance calls. It's not Cosmos3 specific

@lishunyang12 lishunyang12 added the ready label to trigger buildkite CI label Sep 11, 2026
@lishunyang12
lishunyang12 enabled auto-merge (squash) September 11, 2026 20:13
@lishunyang12
lishunyang12 merged commit 13b85c5 into vllm-project:main Sep 11, 2026
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* [Bugfix][Model][Lance] Support decoded video frames in video editing (vllm-project#5128)

Signed-off-by: 吴俊鹏 <248679769+junpengw67-max@users.noreply.github.com>
Co-authored-by: 吴俊鹏 <248679769+junpengw67-max@users.noreply.github.com>

* [Refactor][Diffusion] Remove model-specific names from LoRA and ModelOpt loader defaults (vllm-project#5907)

Signed-off-by: Alicia <115451386+congw729@users.noreply.github.com>
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>

* Optimize CosyVoice3 Stage1 flow batching (vllm-project#4876)

Signed-off-by: gerayking <399geray@gmail.com>
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>

* [3/N] Encode streamed video on the worker with bounded batching (vllm-project#7018)

Signed-off-by: specture724 <specture724@gmail.com>
Co-authored-by: Claude Sonnet 5 <noreply@anthropic.com>
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>

* [Kernel][Boogu-Image] Fuse Q/K RMSNorm + interleaved RoPE via fused_qk_norm_rope (vllm-project#6982)

Signed-off-by: Qihan Kang <rollykanggg@gmail.com>

* [Bugfix][Frontend] Honor output_compression on the image generations route (vllm-project#7447)

Signed-off-by: hsliu_ustc <hsliu_ustc@noreply.gitcode.com>
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
Co-authored-by: amy-why-3459 <wuhaiyan17@huawei.com>

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khairulkabir1661 pushed a commit to khairulkabir1661/vllm-omni that referenced this pull request Sep 25, 2026
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