Verified70% confidenceFactExact time
The KV Cache of a 70B-parameter model with 128K context support can require hundreds of gigabytes of VRAM at full load, exceeding the 80GB VRAM capacity of a single H100.
4
Sources
70%
Confidence
Long-term
Relevance
7/17/2026
First Seen
Sources
Related Claims
UnverifiedFor 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/H100.85% similarVerifiedEven after quantization, 70B-level models often require more than 40 GB of VRAM or a multi-GPU configuration.82% similarVerifiedFor a model with 70B parameters, the KV Cache for an 8K context may occupy several additional gigabytes of VRAM82% similarVerifiedWhen models with hundreds of billions of parameters process a 128K context window, KV Cache can occupy tens of gigabytes of VRAM.80% similarVerifiedTaking 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% similar
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