Unverified50% confidenceFactExact time
Running the same Q8_0 file twice, the second time with q8_0 K/V cache, gives KL 0.0038, a larger effect than quantizing weights from BF16 to Q8_0 (KL 0.0022).
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/17/2026
First Seen
Valid until: 1/15/2027
Sources
Related Entities
Related Claims
UnverifiedQ8_0 means 8-bit integer quantization: weights are stored in 8-bit blocks, each block carrying a scale factor, roughly halving compared with FP16, with very little precision loss but almost no memory savings.73% similarUnverifiedllama.cpp的--cache-type-k q8_0 --cache-type-v q8_0参数可将KV Cache从FP16量化到8-bit，减少约一半缓存显存占用70% similarUnverifiedKV Cache only caches K and V but not Q, because Q is only used in the current step and discarded after use, whereas historical K and V are re-accessed at every subsequent step.68% similarUnverifiedq2_0 belongs to extremely low-bit quantization schemes, representing each weight with only about 2 bits.67% similarUnverifiedThe test used the Swift version's Q5_K_L and the base version's Unsloth Q5_K_XL quantization configurations, both running in 128GB of memory with support for a 262K context, with engrams in Q8_0 stored on SSD.67% similar
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