Verified65% confidenceFactTime unknown
vLLM 和 TensorRT-LLM 等现代推理框架通过连续批处理（Continuous Batching）和 PagedAttention 等技术提升 GPU 利用率
3
Sources
65%
Confidence
Long-term
Relevance
6/1/2026
First Seen
Sources
Hetzner服务器遭大规模冲击：廉价云服务的承载隐忧
twitterlevelsio
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UnverifiedTensorRT-LLM由NVIDIA官方推出，通过算子融合和精度混合计算针对自家GPU进行性能调优，但模型支持范围相对有限76% similarUnverifiedvLLM 支持多 GPU 分布式推理，主要采用张量并行策略，底层集成 Megatron-LM 的并行算子并利用 NCCL 库实现 GPU 间通信75% similarUnverifiedMLX在纯GPU推理时通常有优势，而GGUF在需要CPU/GPU混合调度时更灵活72% similarUnverifiedllama.cpp、Ollama、vLLM等推理框架适配Qwen模型权重，支持GGUF、AWQ、GPTQ等量化格式使其能运行在消费级GPU乃至CPU上72% similarUnverifiedOptimization techniques like PagedAttention, continuous batching, and speculative decoding boosted GPU utilization from 30-50% with traditional methods to over 90%72% similar
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