Release Notes

This section includes the vllm-plugin-FL release information.

v0.2.0

vllm-plugin-FL v0.2.0 requires vllm v0.20.2. Supported platforms: NVIDIA, Hygon DCU.

• Added Features

  • Qwen3.6-35B-A3B model support with text and image inference/serving

  • Qwen3.6-27B model support with text and image inference/serving

  • Hygon DCU platform support with DTK container-based deployment

  • Serving-based test workflow (vllm serve + OpenAI client) for multimodal models

• Improved Features

  • Extended NVIDIA platform test matrix with Qwen3.6 model coverage

  • Updated vLLM compatibility to v0.20.x

v0.1.0

vllm-plugin-FL v0.1.0 requires vllm v0.13.0. Supported platforms: NVIDIA, Ascend, T-Head, MetaX, Iluvatar.

• Added Features

  • Initial release of vllm-plugin-FL as a vLLM inference/serving framework plugin

  • Unified multi-chip backend support via FlagGems and FlagCX integration

  • Flexible operator dispatch system with FlagGems, vendor-specific, and PyTorch reference backends

  • End-to-end verified support for Qwen3.5-397B-A17B, Qwen3-Next-80B-A3B, Qwen3-4B, MiniCPM-o 4.5, GLM-5, Qwen3.5-35B-A3B, and BAAI/bge-m3 models

  • Hardware support for NVIDIA, Ascend, T-Head, MetaX, and Iluvatar chips

  • Platform-specific configuration files (ascend.yaml, cuda.yaml) for auto-detected defaults

  • Environment variable-based configuration for backend selection, vendor filtering, and operator control

  • YAML configuration file support for complete dispatch policy override

  • Multi-process safe operator registry with thread-safe cache operations

• Improved Features

  • Optimized dispatch flow with caching for resolved operators

  • Fallback mechanism from preferred backend to available alternatives on failure

  • Per-operator backend selection order configuration

  • Whitelist and blacklist support for FlagGems and OOT operators

  • Debug logging mode for dispatch system troubleshooting