vLLM v0.1.4stable Released Aug 25, 2023
โš ๏ธ Breaking Change Impact Score: 7/10

vLLM v0.1.4

Source available โ€” automated, not human-reviewed

Component: vllm ยท Channel: stable. Automated analysis, not a compatibility certification. How this works.

Analysis updated: 2026-11-01.

Breaking-change evidence from the source

  • Fix for breaking changes in xformers 0.0.21 by @WoosukKwon in https://github.com/vllm-project/vllm/pull/834
Read the original context โ†—
Source flags breaking changes โ€” review applicability
$ python -m pip install 'vllm==0.1.4'
๐Ÿ“„ .MD
โšก Executive Summary (TL;DR)

vLLM v0.1.4. Source highlight: From now on, vLLM is published with pre-built CUDA binaries. Users don't have to compile the vLLM's CUDA kernels on their machine.

Who Does This Impact? (Role-Based Analysis)

๐Ÿ’ป Software Engineers & Devs

Check the source notes against the package and APIs you use before upgrading.

๐Ÿ“Š Product & Engineering Leads

Use the documented changes to assess relevance to your product; release frequency alone is not a quality measure.

โš™๏ธ DevOps & Security

Verify the target version, runtime requirements and rollback procedure in the official documentation.

โš ๏ธ Breaking Changes & Deprecations (1)

  • Fix for breaking changes in xformers 0.0.21 by @WoosukKwon in https://github.com/vllm-project/vllm/pull/834

โœจ New Features & Capabilities (5)

  • add QWen-7b support
  • add internlm model
  • [Feature | CI] Added a github action to build wheels
  • Add support for aquila
  • Add compute capability 8.9 to default targets

๐Ÿ”ง Bug Fixes & Patches (6)

  • Fix gibberish outputs of GPT-BigCode-based models
  • [Fix] unwantted bias in InternLM Model
  • Fix baichuan doc style
  • Fix typo in tokenizer.py
  • Fix typo in sampling_params.py
  • Fix mqa is false case in gpt_bigcode
๐Ÿ“„ View Raw Release Notes (Original Developer Log)
## Major changes * From now on, vLLM is published with pre-built CUDA binaries. Users don't have to compile the vLLM's CUDA kernels on their machine. * New models: InternLM, Qwen, Aquila. * Optimizing CUDA kernels for paged attention and GELU. * Many bug fixes. ## What's Changed * Fix gibberish outputs of GPT-BigCode-based models by @HermitSun in https://github.com/vllm-project/vllm/pull/676 * [OPTIMIZATION] Optimizes the single_query_cached_kv_attention kernel by @naed90 in https://github.com/vllm-project/vllm/pull/420 * add QWen-7b support by @Sanster in https://github.com/vllm-project/vllm/pull/685 * add internlm model by @gqjia in https://github.com/vllm-project/vllm/pull/528 * Check the max prompt length for the OpenAI completions API by @nicobasile in https://github.com/vllm-project/vllm/pull/472 * [Fix] unwantted bias in InternLM Model by @wangruohui in https://github.com/vllm-project/vllm/pull/740 * Supports tokens and arrays of tokens as inputs to the OpenAI completion API by @wanmok in https://github.com/vllm-project/vllm/pull/715 * Fix baichuan doc style by @UranusSeven in https://github.com/vllm-project/vllm/pull/748 * Fix typo in tokenizer.py by @eltociear in https://github.com/vllm-project/vllm/pull/750 * Align with huggingface Top K sampling by @Abraham-Xu in https://github.com/vllm-project/vllm/pull/753 * explicitly del state by @cauyxy in https://github.com/vllm-project/vllm/pull/784 * Fix typo in sampling_params.py by @wangcx18 in https://github.com/vllm-project/vllm/pull/788 * [Feature | CI] Added a github action to build wheels by @Danielkinz in https://github.com/vllm-project/vllm/pull/746 * set default coompute capability according to cuda version by @zxdvd in https://github.com/vllm-project/vllm/pull/773 * Fix mqa is false case in gpt_bigcode by @zhaoyang-star in https://github.com/vllm-project/vllm/pull/806 * Add support for aquila by @shunxing1234 in https://github.com/vllm-project/vllm/pull/663 * Update Supported Model List by @zhuohan123 in https://github.com/vllm-project/vllm/pull/825 * Fix 'GPTBigCodeForCausalLM' object has no attribute 'tensor_model_parallel_world_size' by @HermitSun in https://github.com/vllm-project/vllm/pull/827 * Add compute capability 8.9 to default targets by @WoosukKwon in https://github.com/vllm-project/vllm/pull/829 * Implement approximate GELU kernels by @WoosukKwon in https://github.com/vllm-project/vllm/pull/828 * Fix typo of Aquila in README.md by @ftgreat in https://github.com/vllm-project/vllm/pull/836 * Fix for breaking changes in xformers 0.0.21 by @WoosukKwon in https://github.com/vllm-project/vllm/pull/834 * Clean up code by @wenjun93 in https://github.com/vllm-project/vllm/pull/844 * Set replacement=True in torch.multinomial by @WoosukKwon in https://github.com/vllm-project/vllm/pull/858 * Bump up the version to v0.1.4 by @WoosukKwon in https://github.com/vllm-project/vllm/pull/846 ## New Contributors * @naed90 made their first contribution in https://github.com/vllm-project/vllm/pull/420 * @gqjia made their first contribution in https://github.com/vllm-project/vllm/pull/528 * @nicobasile made their first contribution in https://github.com/vllm-project/vllm/pull/472 * @wanmok made their first contribution in https://github.com/vllm-project/vllm/pull/715 * @UranusSeven made their first contribution in https://github.com/vllm-project/vllm/pull/748 * @eltociear made their first contribution in https://github.com/vllm-project/vllm/pull/750 * @Abraham-Xu made their first contribution in https://github.com/vllm-project/vllm/pull/753 * @cauyxy made their first contribution in https://github.com/vllm-project/vllm/pull/784 * @wangcx18 made their first contribution in https://github.com/vllm-project/vllm/pull/788 * @Danielkinz made their first contribution in https://github.com/vllm-project/vllm/pull/746 * @zhaoyang-star made their first contribution in https://github.com/vllm-project/vllm/pull/806 * @shunxing1234 made their first contribution in https://github.com/vllm-project/vllm/pull/663 * @ftgreat made their first contribution in https://github.com/vllm-project/vllm/pull/836 * @wenjun93 made their first contribution in https://github.com/vllm-project/vllm/pull/844 **Full Changelog**: https://github.com/vllm-project/vllm/compare/v0.1.3...v0.1.4