Unverified50% confidenceFactExact time
Llama 3.1 70B uses 8 KV heads instead of 64 attention heads, reducing the KV cache size to about one-eighth of the original.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/18/2026
First Seen
Valid until: 1/16/2027
Sources
Related Entities
Related Claims
UnverifiedMLA（Multi-head Latent Attention）通过低秩压缩将 KV 缓存的显存占用降低至传统 MHA 的约 1/873% similarUnverifiedEnabling the MTP draft head introduces additional attention layer KV requirements, reducing the token capacity available for the KV cache from 767,317 to 592,164, a decrease of about 23%.70% similarVerifiedMulti-head Latent Attention (MLA) compresses storage by projecting KV into a low-dimensional latent space, reducing KV Cache memory usage to 5% to 13% of that of traditional methods.70% similarUnverifiedAdopting sparse attention can compress the KV cache to approximately 1/4, supporting approximately 4 times the context length of full attention under the same memory budget.70% similarUnverifiedTaking the LLaMA-3 70B model as an example, with 80 layers, head_dim=128, and BF16 precision, each token occupies approximately 80KB of KV cache.70% similar
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