[Model][MiniMax-M3] Add pipeline parallelism support

[soaringk]

Purpose

Adds pipeline-parallelism (PP) support to MiniMax-M3.

Fixes #45455. Relates to #45668.

Changes

• Implement SupportsPP for MiniMaxM3SparseForCausalLM and
  MiniMaxM3SparseForConditionalGeneration.
• Add PP first/last-rank handling for embed_tokens, final norm, and lm_head.
• Thread intermediate_tensors through the MiniMax-M3 text and VL wrappers.
• Update docs/models/supported_models.md for MiniMax-M3 PP support.

Single-GPU and tensor-parallel paths are unchanged for pp=1.

Test plan & results

Runtime validated previously with real MiniMaxAI/MiniMax-M3-MXFP8 weights:

• pp=4, tp=1: passed; generated correct output for "The capital of France is".
• pp=7: passed.
• Dummy-weight wiring check: passed at pp=2 and pp=5.

Additional local check:

• git diff --check

Not a duplicate

No open PR adds PP support to MiniMax-M3. Checked 45455 in:body, keyword
MiniMax-M3 pipeline, and open MiniMax-M3 PRs.

AI assistance

AI assistance was used. The submitter reviewed the changed lines and ran the
checks listed above.

[soaringk]

Thanks for the report, @RodriMora. This wires the SupportsPP interface into MiniMax-M3 (text + VL, NVIDIA + ROCm) so pipeline_parallel_size>1 works.

cc @youkaichao @Isotr0py @functionstackx (M3 authors) — would appreciate a review when you have a chance.

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[soaringk]

Friendly ping @Isotr0py @youkaichao — could one of you review or route this PR when you have a chance?

This is a small 2-file MiniMax-M3 PP wiring change, fixes #45455, mirrors the existing MiniMax-M2 PP implementation, and was runtime-validated with real weights at pp=4/pp=7. If there is a better model/PP owner for this, please point me to them.

[Isotr0py]

Hmmm, I have just launched the MXFP8 model against this PR with PP=4, but seems it still doesn't work:

[04:27 PM]-[mozf@gb200-rack1-18]-[~/vllm]- |minimax-m3-pp → soaringk ?:5 ✗|
$ vllm serve MiniMaxAI/MiniMax-M3-MXFP8 --trust-remote-code --pipeline-parallel-size 4      --gpu-memory-utilization 0.80     --block-size 128     --attention-backend FLASH_ATTN     --no-enable-prefix-caching --mm-encoder-tp-mode data --max-model-len 32768
(APIServer pid=1973596) INFO 06-21 16:28:22 [api_utils.py:339] 
(APIServer pid=1973596) INFO 06-21 16:28:22 [api_utils.py:339]        █     █     █▄   ▄█
(APIServer pid=1973596) INFO 06-21 16:28:22 [api_utils.py:339]  ▄▄ ▄█ █     █     █ ▀▄▀ █  version 0.23.1rc1.dev90+gb09977fdb
(APIServer pid=1973596) INFO 06-21 16:28:22 [api_utils.py:339]   █▄█▀ █     █     █     █  model   MiniMaxAI/MiniMax-M3-MXFP8
(APIServer pid=1973596) INFO 06-21 16:28:22 [api_utils.py:339]    ▀▀  ▀▀▀▀▀ ▀▀▀▀▀ ▀     ▀
(APIServer pid=1973596) INFO 06-21 16:28:22 [api_utils.py:339] 
(APIServer pid=1973596) INFO 06-21 16:28:22 [api_utils.py:273] non-default args: {'model_tag': 'MiniMaxAI/MiniMax-M3-MXFP8', 'model': 'MiniMaxAI/MiniMax-M3-MXFP8', 'trust_remote_code': True, 'max_model_len': 32768, 'attention_backend': 'FLASH_ATTN', 'pipeline_parallel_size': 4, 'block_size': 128, 'gpu_memory_utilization': 0.8, 'enable_prefix_caching': False, 'mm_encoder_tp_mode': 'data'}
(APIServer pid=1973596) INFO 06-21 16:28:22 [arg_utils.py:762] HF_HUB_OFFLINE is True, replace model_id [MiniMaxAI/MiniMax-M3-MXFP8] to model_path [/mnt/lustre/hf-models/hub/models--MiniMaxAI--MiniMax-M3-MXFP8/snapshots/1c4e6a69f3278df8dd6c9693fcca241efe439b7d]
(APIServer pid=1973596) INFO 06-21 16:28:22 [model.py:598] Resolved architecture: MiniMaxM3SparseForConditionalGeneration
(APIServer pid=1973596) INFO 06-21 16:28:22 [model.py:1723] Using max model len 32768
(APIServer pid=1973596) INFO 06-21 16:28:24 [scheduler.py:252] Chunked prefill is enabled with max_num_batched_tokens=8192.
(APIServer pid=1973596) Traceback (most recent call last):
(APIServer pid=1973596)   File "/home/mozf/vllm/.venv/bin/vllm", line 10, in <module>
(APIServer pid=1973596)     sys.exit(main())
(APIServer pid=1973596)              ^^^^^^
(APIServer pid=1973596)   File "/home/mozf/vllm/vllm/entrypoints/cli/main.py", line 95, in main
(APIServer pid=1973596)     args.dispatch_function(args)
(APIServer pid=1973596)   File "/home/mozf/vllm/vllm/entrypoints/cli/serve.py", line 148, in cmd
(APIServer pid=1973596)     uvloop.run(run_server(args))
(APIServer pid=1973596)   File "/home/mozf/vllm/.venv/lib/python3.12/site-packages/uvloop/__init__.py", line 96, in run
(APIServer pid=1973596)     return __asyncio.run(
(APIServer pid=1973596)            ^^^^^^^^^^^^^^
(APIServer pid=1973596)   File "/usr/lib/python3.12/asyncio/runners.py", line 194, in run
(APIServer pid=1973596)     return runner.run(main)
(APIServer pid=1973596)            ^^^^^^^^^^^^^^^^
(APIServer pid=1973596)   File "/usr/lib/python3.12/asyncio/runners.py", line 118, in run
(APIServer pid=1973596)     return self._loop.run_until_complete(task)
(APIServer pid=1973596)            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1973596)   File "uvloop/loop.pyx", line 1518, in uvloop.loop.Loop.run_until_complete
(APIServer pid=1973596)   File "/home/mozf/vllm/.venv/lib/python3.12/site-packages/uvloop/__init__.py", line 48, in wrapper
(APIServer pid=1973596)     return await main
(APIServer pid=1973596)            ^^^^^^^^^^
(APIServer pid=1973596)   File "/home/mozf/vllm/vllm/entrypoints/openai/api_server.py", line 658, in run_server
(APIServer pid=1973596)     await run_server_worker(listen_address, sock, args, **uvicorn_kwargs)
(APIServer pid=1973596)   File "/home/mozf/vllm/vllm/entrypoints/openai/api_server.py", line 672, in run_server_worker
(APIServer pid=1973596)     async with build_async_engine_client(
(APIServer pid=1973596)   File "/usr/lib/python3.12/contextlib.py", line 210, in __aenter__
(APIServer pid=1973596)     return await anext(self.gen)
(APIServer pid=1973596)            ^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1973596)   File "/home/mozf/vllm/vllm/entrypoints/openai/api_server.py", line 99, in build_async_engine_client
(APIServer pid=1973596)     async with build_async_engine_client_from_engine_args(
(APIServer pid=1973596)   File "/usr/lib/python3.12/contextlib.py", line 210, in __aenter__
(APIServer pid=1973596)     return await anext(self.gen)
(APIServer pid=1973596)            ^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1973596)   File "/home/mozf/vllm/vllm/entrypoints/openai/api_server.py", line 123, in build_async_engine_client_from_engine_args
(APIServer pid=1973596)     vllm_config = engine_args.create_engine_config(usage_context=usage_context)
(APIServer pid=1973596)                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1973596)   File "/home/mozf/vllm/vllm/engine/arg_utils.py", line 2255, in create_engine_config
(APIServer pid=1973596)     config = VllmConfig(
(APIServer pid=1973596)              ^^^^^^^^^^^
(APIServer pid=1973596)   File "/home/mozf/vllm/.venv/lib/python3.12/site-packages/pydantic/_internal/_dataclasses.py", line 121, in __init__
(APIServer pid=1973596)     s.__pydantic_validator__.validate_python(ArgsKwargs(args, kwargs), self_instance=s)
(APIServer pid=1973596)   File "/home/mozf/vllm/vllm/config/vllm.py", line 876, in __post_init__
(APIServer pid=1973596)     self.model_config.verify_with_parallel_config(self.parallel_config)
(APIServer pid=1973596)   File "/home/mozf/vllm/vllm/config/model.py", line 1177, in verify_with_parallel_config
(APIServer pid=1973596)     raise NotImplementedError(
(APIServer pid=1973596) NotImplementedError: Pipeline parallelism is not supported for this model. Supported models implement the `SupportsPP` interface.

[mergify]

Documentation preview: https://vllm--45810.org.readthedocs.build/en/45810/

[soaringk]

Thanks for testing. I pushed 000ef96 with a follow-up fix for the config-time SupportsPP check and the requested docs update.

The runtime failure can happen before model construction if model-info cache metadata still says the architecture does not support PP. The new commit makes package-style model registrations include package submodules in the model-info cache key, so interface metadata is invalidated when the implementation changes under a re-exporting package entry point.

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @soaringk.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[soaringk]

@Isotr0py Thanks for testing. The startup failure may be from stale model-info cache metadata: MiniMax-M3 is registered through a package entry point, while the PP change is in submodules. I added a follow-up cache-key fix so package-style registrations invalidate cached capability metadata when submodules change.

Which direction would you prefer?

1. Keep the cache fix in this PR.
2. Split it into a separate PR. If so, could you please clear the local modelinfos cache and retry this PR without that follow-up?

[Isotr0py]

Let's split cache fix into another PR :)

[soaringk]

@Isotr0py Thanks, agreed. I split the model-info cache fix out of this PR.
This PR now only keeps the MiniMax-M3 PP changes and docs update.

Could you please clear the local modelinfos cache and retry this PR?

[mergify]

Hi @soaringk, the pre-commit checks have failed. Please run:

uv pip install pre-commit>=4.5.1
pre-commit install
pre-commit run --all-files

Then, commit the changes and push to your branch.

For future commits, pre-commit will run automatically on changed files before each commit.

[soaringk]

@Isotr0py It looks like Buildkite #73930 is waiting for approval. Could you help approve the remaining CI steps when you have a chance?