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
- Split compressed_tensors_moe.py into separate wna16, int8, fp8, nvfp4
- [TPU] Add numba dependency to tpu requirements.
- [Feature][Responses API] Support logprobs
- [Bug]: Missing tokens while streaming when using gpt-oss-20b
- [Feature] DCCP supported
- [CI]: Declarative regression tests for API parameters
- [Sampler] Support for distributed sampling for topk_topp_sampler across ranks
- [bug fix] disable memory pool to release unused `bf16` weights
- Support using SigLIP2 text and image embedding as standalone model
- [Feat] support fp8 quantization in update weights
- Docs
- Python not yet supported