vllm
https://github.com/vllm-project/vllm
Python
A high-throughput and memory-efficient inference and serving engine for LLMs
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- Issues
- [V1][Spec Decode][Feature] support tree attention in flash-linear-attenton
- [Bug]: Error occurred when I run an simple command: "TORCH_USE_CUDA_DSA=1 LMCACHE_CHUNK_SIZE=8 vllm serve /home/nbw/model/Qwen2-0.5B/ --port 8000 --kv-transfer-config '{"kv_connector":"LMCacheConnectorV1", "kv_role":"kv_both"}'"
- [Bug]: weights_not_loaded check failed when loading bf16 DeepSeek-V3.2-Exp
- [Feature]: Multi-Adapter Support for Embed Qwen3 8B Embedding Model
- [Feature]: Default eplb num_redundant_experts to the lowest valid value if unspecified
- [Feature]: MCP Support for Non Harmony Models
- [Feature]: Could you please provide Chinese documentation for vLLM? 😊
- [EPLB] perf: optimize balanced packing with min-heap (O(n) → O(log n))
- [Build] Use pip constraints to pin dependency versions
- [Bug]: gpt-oss response api: streaming + code interpreter has bugs
- Docs
- Python not yet supported