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
- [Test][V1] Cover input-queue arrivals during uncapped prefill
- [Kernel][XPU] Mamba2 SSD: tensor-descriptor path for _chunk_scan_fwd_kernel and _chunk_state_fwd_kernel
- [Bug]: DeepSeek-V4.1-Flash worker dies with `CUDA error: unspecified launch failure` during long-context decode with dspark spec decode (DP=3, TP=2, EP); Anthropic `/v1/messages` adapter then fails on the error chunk
- [Bugfix][Attention] Fall back when FlashInfer attention JIT is unavailable
- [Bugfix] Preserve timed-trace chunk identity across benchmark runs
- [Feature]: Allow pooling tasks (token_embed / token_classify) to reuse prefix cache while returning full hidden-state sequences
- [Frontend] Add completion SSE on top of packed top-k logprobs
- [Bugfix][Core] Reclaim parked streaming sessions in reset_prefix_cache
- [ROCm] ROCm binding on common Kimi-K3 Dspark MLA module
- [ROCm] Enable tuned AITER per-token FP8 linear on RDNA4 (a8w8 on RDNA3 WIP)
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