Unverified50% confidenceFactExact time
FP8 KV cache halves both the memory footprint of concurrent sequences and the number of bytes moved over the network.
1
Sources
50%
Confidence
Long-term
Relevance
10/19/2026
First Seen
Sources
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Related Claims
UnverifiedFP8 KV cache is a quantization technique that compresses the Key-Value cache in the attention mechanism from FP16 or BF16 to 8 bits, which can halve the GPU memory usage of the KV cache80% similarUnverifiedReducing the KV cache from FP16 to INT8 saves 50% of VRAM, and reducing it to INT4 saves 75%.78% similarVerifiedPrompt caching saves pre-computed KV matrices on the server side, reducing the processing of repeated prefixes from O(n²) to O(1) cache reads, enabling up to 90% compression in latency and cost.73% similarUnverifiedThe KV cache degrades the per-step matrix multiplication from large matrix times large matrix to vector times matrix, sharply reducing the amount of computation, but all cached K/V must be read in, so arithmetic intensity drops substantially and the performance bottleneck shifts from SM compute units to fixed overheads such as HBM bandwidth and kernel launches.71% similarVerifiedQuantized KV caches (such as storing KV vectors in FP8 or INT4) can compress the cache size to 1/2 or even 1/4 of the original.71% similar
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