Replaces standard inference engines with a high-throughput serving system utilizing PagedAttention for efficient memory management. Delivers state-of-the-art serving speed and continuous batching for large language models on GPU hardware.
Tech Stack
PythonAI, ML & Data
Why vllm?
• Extremely high throughput
• Efficient KV cache management
• Easy HuggingFace integration
Limitations
• Requires specific GPU hardware
• Complex CUDA dependencies
• Rapidly changing API
3/6/2026
Last Update
13,991
Forks
3,537
Issues
Apache-2.0
License
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