vLLM
High-throughput LLM serving with PagedAttention
F
Score: 35/100
Type
Execution
jit
Interface
api
About
vLLM is a high-throughput and memory-efficient inference engine for LLMs. It features PagedAttention for efficient KV cache management, continuous batching, and optimized CUDA kernels. Ideal for production serving with OpenAI-compatible API.
Performance
5000ms
Cold Start
2000MB
Base Memory
3000ms
Startup Overhead
✓ Last Verified
Date: Jan 18, 2026
Method: manual test
Manually verified
Languages
Python
Details
- Isolation
- process
- Maturity
- production
- License
- Apache-2.0