Unverified50% confidenceFactExact time
KV sharing can be combined with low-precision KV cache quantization, including fp8, mxfp8 and nvfp4.
1
Sources
50%
Confidence
Long-term
Relevance
10/23/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedvLLM supports FP8 KV Cache, a key optimization.74% similarUnverifiedvLLM's `fp8` KV cache format corresponds to E4M3 and offers three calibration methods: no calibration (scaling factor defaults to 1.0), random-token warmup, and dataset calibration via llm-compressor.72% similarUnverifiedGLM-5.3 supports full 1M context using FP8 KV cache.71% similarVerifiedKV Cache technology caches the already-computed K and V matrices in GPU memory, which can improve inference speed by several times69% similarUnverifiedThe solution uses BF16 precision uniformly for the KV cache, and MXFP4 quantization for the model weights.66% similar
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