Unverified50% confidenceFactExact time
The prefill stage is a compute-intensive operation primarily limited by GPU compute, while the decode stage is a memory-bandwidth-intensive operation primarily limited by VRAM bandwidth.
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9/12/2026
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UnverifiedThe bottleneck of traditional autoregressive decoding lies in memory bandwidth rather than compute capability, resulting in low GPU utilization.78% similarUnverifiedThe Prefill stage of LLM inference is compute-intensive with GPU utilization close to 100%, while the Decode stage is memory-bandwidth-intensive with the bottleneck being HBM VRAM bandwidth.76% similarUnverifiedFor modern CPUs and GPUs, memory bandwidth is often the true bottleneck for inference speed rather than the compute units' arithmetic throughput, which is why quantization can bring speed improvements.76% similar
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