Unverified85% confidenceFactTime unknown
经过SVDQuant的4-bit量化后,FLUX模型显存需求可从约24GB降至约6GB
1
Sources
85%
Confidence
Long-term
Relevance
6/1/2026
First Seen
Sources
SVDQuant:4-bit量化让扩散模型在消费级GPU上高效运行
githubnunchaku-ai
Related Entities
Related Claims
Unverified140GB的FP16 70B模型经4-bit量化后可压缩至约35-40GB,通信开销降低约75%;2-bit量化可压缩至约18GB但带来精度损失76% similarUnverifiedINT4 量化模型有望在 8GB 乃至更低显存的显卡上完成原本需要 16GB 或 24GB 显存的模型推理75% similarUnverifiedOllama 默认使用 Q4_K_M 等量化方案,将 31B 参数模型的显存需求从约 62GB(FP16)降低到约 20GB75% similarUnverifiedQ3_K_M将每个权重压缩至约3bit,27B模型权重体积可降至约12~13GB75% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/28966API
curl https://kongchang.com/api/v1/knowledge/claims/28966MCP
get_claim(id=28966)