cohere(@cohere)
Excited to share our work on production-ready W4A8 inference, now integrated in vLLM! By combining 4...
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TL;DR · AI 摘要
Cohere实现了生产级W4A8推理优化，并集成到vLLM中，显著提升性能。
核心要点
- 结合4-bit权重和8-bit激活实现内存与计算平衡。
- 相比W4A16，TTFT提升58%，TPOT提升45%。
- 优化方案已集成至开源项目vLLM。
#推理优化#vLLM#Cohere#机器学习
打开原文Cohere on X: "Excited to share our work on production-ready W4A8 inference, now integrated in vLLM! By combining 4-bit weights (low memory) with 8-bit activations (high compute), we hit the sweet spot for both decoding and prefill — up to 58% faster TTFT and 45% faster TPOT vs W4A16 on Hopper. https://t.co/M37wT5KS8Z" / X
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Excited to share our work on production-ready W4A8 inference, now integrated in vLLM! By combining 4-bit weights (low memory) with 8-bit activations (high compute), we hit the sweet spot for both decoding and prefill — up to 58% faster TTFT and 45% faster TPOT vs W4A16 on Hopper.
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