Unverified60% confidenceFactExact time
Reducing the KV cache from FP16 to INT8 saves 50% of VRAM, and reducing it to INT4 saves 75%.
2
Sources
60%
Confidence
Long-term
Relevance
7/16/2026
First Seen
Sources
Related Claims
UnverifiedChoosing Q4_0 for KV cache quantization can compress the cache size to approximately one-quarter of FP16, with far less impact on output quality than model weight quantization.79% similarUnverifiedThe quantized MLX KV cache reduces prompt memory usage by up to 74% compared to before.75% similarUnverifiedIn KV caching, cache writes are usually about 25% more expensive than ordinary input tokens, but cache reads are about 90% cheaper.72% similarUnverifiedGQA groups attention heads to share KV projections, which can compress the KV cache to 1/4 or less of the original size with almost no loss in model quality.72% 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.72% similar
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