Verified65% confidenceFactTime unknown
32B参数规模的模型在量化后通常可以压缩到约16-20GB显存占用，一张NVIDIA RTX 4090（24GB显存）就能运行
3
Sources
65%
Confidence
Long-term
Relevance
6/1/2026
First Seen
Sources
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Related Claims
UnverifiedThe RTX 4090 has 24 GB of VRAM, and after loading the 27B Q4 model, there is typically enough space remaining to support a context of 30,000–40,000 tokens.84% similarVerified一个原本需要60GB显存的30B参数模型，经过量化后能在16GB甚至8GB显存的消费级显卡上运行82% similarVerifiedA 70B-parameter FP16 model requires approximately 140 GB of video memory, approximately 70 GB after INT8 quantization, and approximately 35–40 GB after INT4 quantization.80% similarUnverifiedA 140 GB FP16 70B model can be compressed to approximately 35–40 GB after 4-bit quantization, reducing communication overhead by about 75%; 2-bit quantization can compress it to approximately 18 GB but introduces accuracy loss.80% similar
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