Verified75% confidenceBenchmarkExact time
Taking the LLaMA-2 70B model as an example, a sequence of 2048 tokens requires approximately 4 GB of VRAM for the KV cache alone.
3
Sources
75%
Confidence
Long-term
Relevance
7/20/2026
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.80% similarUnverifiedFor 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.78% similarUnverifiedFor a 32-layer, 4096-dimensional model, the KV Cache for processing 2048 tokens occupies approximately 1 GB of VRAM78% similarUnverifiedTaking Llama-3 70B as an example, the prefill stage for processing 32K tokens on an A100 80GB GPU takes approximately 800–1200ms, while processing 2K tokens takes only about 50ms.76% 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.74% similar
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