๊ฐ€์ž… ํ›„ ์ดˆ๋Œ€ ๋งํฌ๋ฅผ ๊ณต์œ ํ•˜๋ฉด ๋™์˜์ƒ ์žฌ์ƒ ๋ฐ ์ดˆ๋Œ€ ๋ณด์ƒ์„ ๋ฐ›์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

vLLM
@vllm_project
A high-throughput and memory-efficient inference and serving engine for LLMs. Join to discuss together with the community!
๊ฐ€์ž… March 2024
36 ํŒ”๋กœ์ž‰ ์ค‘    45.4K ํŒฌ
5x lower token costs on DeepSeek V4 in one month! Highlighting the vLLM community at work: day-zero recipes, then relentless optimization across kernels, scheduling, and serving. Every PR counts. ๐Ÿš€
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๐Ÿ’ก Continuous software innovation is the force multiplier behind AI infrastructure โ€” compounding inference performance, lowering cost per token, and increasing long-term value with every optimization. Open source accelerates this advantage. Leading AI frameworks like @PyTorch and inference engines such as @sgl_project and @vllm_project are built natively on NVIDIA CUDA, enabling research breakthroughs and software optimizations to unlock great performance on NVIDIA GPUs from day zero.
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