Verified65% confidenceBenchmarkExact time
Quantization formats can compress the runtime memory of a 70B-parameter model from 140 GB to under 40 GB.
3
Sources
65%
Confidence
Long-term
Relevance
7/24/2026
First Seen
Sources
TradingSpy：本地优先开源AI交易助手，数据隐私不妥协
hackernewshackernews7/11/2026
Related Claims
UnverifiedQuantization can compress the storage size of a 70-billion-parameter model from approximately 140 GB in FP16 to approximately 35–40 GB in INT4, enabling it to run on consumer-grade hardware such as a single RTX 4090 with CPU memory offloading.84% similarVerified4-bit quantization compresses each parameter to 0.5 bytes, theoretically compressing 140GB down to approximately 35–40GB.83% similarVerifiedEven after quantization, 70B-level models often require more than 40 GB of VRAM or a multi-GPU configuration.78% similarVerifiedThe 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 H100.77% similar
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