Verified80% confidenceBenchmarkExact time
Taking 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.
4
Sources
80%
Confidence
Long-term
Relevance
7/15/2026
First Seen
Sources
Related Claims
VerifiedLLaMA-2-70B's KV Cache for a single request at a context length of 128K can occupy more than 160 GB of VRAM.82% similarUnverifiedFor 1 million tokens, the KV Cache alone can consume hundreds of GB of VRAM at FP16 precision, far exceeding the 80 GB capacity limit of a single A100/H100.82% similarVerifiedWhen the context length is extended to one million tokens, the KV Cache itself can occupy tens of gigabytes of VRAM.81% 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.80% similarUnverifiedFor a 32-layer, 4096-dimensional model, the KV Cache for processing 2048 tokens occupies approximately 1 GB of VRAM80% similar
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