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
- [WIP][XPU][Test]add xpu yaml
- [V1][Core] Add public build_full_block_hash_chain helper for offline prefix-cache analysis
- [Bug]: [MRV2] MTP speculative decoding crashes with cudaErrorStreamCaptureUnsupported during CUDA graph capture
- [Kernel] ReplaySSM: cache SSM inputs for faster Gated DeltaNet standard decode
- [Bugfix] Fix int4_per_token_head for SWA models and gemma 4
- [Bug]: Gemma4 MTP speculative decoding crashes at engine init on 0.25.1 — "a and b must have same reduction dim" (regression from 0.21.0)
- [Bug]: sample_tokens RPC timeout with GLM-5.2-FP8 + DSpark speculative decoding, TP=8 across 2 nodes (Blackwell GB200)
- [RFC]: Context-length-aware speculative token scheduling — extending num_speculative_tokens_per_batch_size with a context-length axis
- `NixlPushMode` Roadmap - Reliability Issue Inventory
- [Perf][Kernel] Fused DSA indexer Top-k kernel (LiteTopk)
- Docs
- Python not yet supported