Unverified50% confidenceBenchmarkExact time
Compressing DeepSeek Coder to 2-bit loses 67% of passing solutions, whereas the 4-bit version sacrifices only 2% for a 70% reduction in size.
1
Sources
50%
Confidence
Long-term
Relevance
9/16/2026
First Seen
Sources
Related Entities
Related Claims
Unverified13B–14B class models (4-bit quantization) see speeds drop to 2–5 tokens per second under this configuration73% 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.70% similarUnverified三值化权重每个权重仅携带约1.58 bits信息量（log₂3≈1.585），相比FP32的32 bits信息密度下降约20倍69% similarUnverified双编码器通常将语义压缩为768维向量，该数字来源于BERT-base的隐藏层大小，工业部署中常压缩到128或256维68% similarVerifiedEven compressing the weights to 214GB using 4-bit quantization still far exceeds the capacity of a single 48GB GPU.67% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/925952API
curl https://kongchang.com/api/v1/knowledge/claims/925952MCP
get_claim(id=925952)