[Model] Add Qwen3.5 hybrid model support

[liuchenbing2026]

Add inference support for the Qwen3.5 hybrid architecture model, which interleaves full attention (transformer) and linear attention (Gated Delta Net) layers with dense MLP.

New files:

• vllm/transformers_utils/configs/qwen3_5.py: Qwen3_5TextConfig with head_dim=256, partial_rotary_factor=0.25, and hybrid layer_types
• vllm/model_executor/models/qwen3_5.py: Full model implementation including Qwen3_5GatedDeltaNet with separate input projections (in_proj_qkv, in_proj_z, in_proj_b, in_proj_a), dense MLP (no MoE), hybrid decoder layer, custom op registration, and weight loading with multimodal (language_model prefix) support

Modified files:

• Register Qwen3_5TextConfig in config registry (model_type: qwen3_5_text)
• Register Qwen3_5ForCausalLM in model registry

Purpose

Test Plan

Test Result

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Essential Elements of an Effective PR Description Checklist

• 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.
• 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.
• (Optional) Release notes update. If your change is user facing, please update the release notes draft in the Google Doc.

[gemini-code-assist]

Code Review

This pull request introduces support for the Qwen3.5 hybrid model architecture. The implementation is well-structured, reusing components from Qwen3-Next where appropriate and adding new modules like Qwen3_5GatedDeltaNet for the model's specific characteristics. The changes include the model definition, its configuration, and registration within the vLLM framework. The code largely follows existing patterns, but I've identified one issue with an incorrect type hint that should be addressed for correctness and consistency.

[gemini-code-assist]

The return type hint for get_mamba_state_shape_from_config is incorrect. It is specified as tuple[tuple[int, int], tuple[int, int]], but the MambaStateShapeCalculator.gated_delta_net_state_shape function it calls returns a tuple where the second element is a 3-tuple (num_heads, head_v_dim, head_k_dim). The correct return type should be tuple[tuple[int, int], tuple[int, int, int]] to match the actual returned value and the base class IsHybrid.

Suggested change

	def get_mamba_state_shape_from_config(
	cls, vllm_config: "VllmConfig"
	) -> tuple[tuple[int, int], tuple[int, int]]:
	def get_mamba_state_shape_from_config(
	cls, vllm_config: "VllmConfig"
	) -> tuple[tuple[int, int], tuple[int, int, int]]:

[DarkLight1337]

We already have another open PR for this: #34110

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @liuchen2026fly.

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

[DarkLight1337]

Closing as superseded by #34110