vllm-project/vllm-omni
A framework for efficient model inference with omni-modality models
- Stars
- 7.3k
- Forks
- 1.9k
- Open issues
- 906
- Last push
- today
About vllm-omni
vllm-omni is a free, open-source AI inference tool by vllm-project, written mainly in Python. A framework for efficient model inference with omni-modality models. It has 7.3k GitHub stars and 1.9k forks, and was last updated today. It's released under the Apache-2.0 license, a standard open-source license.
- License
- Apache-2.0
- Language
- Python
- Stars
- 7,297
- Last update
- today
- Runs on Mac
- Not stated
- GPU
- Not stated
- Paid API key
- Not required
- Self-hostable
- Not stated
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vllm-omni FAQ
Is vllm-omni free?
Yes. vllm-omni is open source and free to use. It's released under the Apache-2.0 license, a standard open-source license.
Does vllm-omni run on a Mac?
Its README doesn't say. Check the installation guide on GitHub before you start.
Does vllm-omni need a GPU?
Its README doesn't state hardware needs. AI models generally run much faster with a GPU.
Is vllm-omni still maintained?
Yes. It was last updated today and has 906 open issues on GitHub.
What are alternatives to vllm-omni?
Similar free, open-source tools include vllm, BentoML, sglang, TensorRT-LLM.