Unverified50% confidenceFactExact time
Running a 16-bit precision 70B model on 2×80GB GPUs leaves only 2.9 GB of VRAM after the weights are loaded, accommodating only about 9,000 in-flight tokens, which in practice cannot serve requests effectively.
1
Sources
50%
Confidence
Long-term
Relevance
10/13/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedTaking a 70B parameter model with FP16 precision and 32 attention head layers as an example, the KV Cache for a single 200K-length request requires approximately 80–120 GB of VRAM, far exceeding the 80 GB VRAM limit of a single A100 GPU.78% similarVerifiedThe VRAM capacity ceiling of a single A100 GPU is 80GB76% similarUnverifiedCompressing the context from 128K to 32K may quadruple the number of concurrent users a single GPU can serve, representing a trade-off between throughput and context length.76% similarUnverifiedGPT-OSS 120B需要大于80GB显存（如H100 GPU）才能运行76% similarUnverifiedRunning a 70B model locally requires at minimum a professional GPU with 48GB of VRAM, such as an NVIDIA A6000 or dual RTX 4090 cards.75% similar
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