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
- [Model] Support ModernBERT decoder (Ettin) via the Transformers modeling backend
- [Core] Shared abstractions for specialized decode kernels
- [Perf][DSv4.1] Fuse C1/C2 compression with FP8 KV cache insertion
- [ROCm][CI][BugFix][AITER ON] Make LM Eval Small Models tests pass on MI300/MI355 and ensure they can work with vllm serve and vllm bench serve with AITER on and off
- [Perf][Attention] DiffKV prefill tiling on SM80: BLOCK_M=128 + KV tile 64 gives 3.0x on 200K-context chunks
- WIP: [Bugfix][Model] Preserve all Kimi-Audio embeddings in batched requests
- WIP: [Bugfix][ROCm] Preserve 64-bit QuickReduce phase offsets
- [Bug]: Severe output degeneration on SM120 with Apertus-70B FP8 in vLLM 0.25.1; v0.22.1 works after rollback
- [Bugfix][Spec Decode] Support dynamic speculative decoding in ngram_gpu (#60981)
- [Docs][Distributed] Document GLOO_SOCKET_IFNAME for docker pipeline parallel deployments (#59109)
- Docs
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