Unverified60% confidenceFactExact time
For the LLaMA-2 70B model, when processing a context of 4096 tokens, the KV Cache requires approximately 20 GB of system memory at FP16 precision.
2
Sources
60%
Confidence
Long-term
Relevance
7/19/2026
First Seen
Sources
Related Claims
VerifiedTaking LLaMA-2 70B as an example, when processing a 4096-token context with a batch size of 32, the KV Cache can consume over 80 GB of memory.79% similarVerifiedLLaMA-2 7B's KV Cache occupies approximately 2 GB with a 4096-token context, and can surge to over 16 GB when extended to a 32K context79% similarVerifiedTaking the LLaMA-2 70B model as an example, a sequence of 2048 tokens requires approximately 4 GB of VRAM for the KV cache alone.78% similarVerifiedLLaMA-2-70B's KV Cache for a single request at a context length of 128K can occupy more than 160 GB of VRAM.78% similarVerifiedThe VRAM usage of KV Cache grows linearly with sequence length; for a 70-billion-parameter model using GQA, the KV Cache usage can reach tens of GB when processing 100,000 tokens.78% similar
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