Unverified50% confidenceFactExact time
1-bit量化（BitNet）将每个权重压缩为单个比特，仅表示+1或-1
1
Sources
50%
Confidence
Long-term
Relevance
7/20/2026
First Seen
Sources
Related Claims
Unverified1-bit LLM 的核心思路是将模型权重压缩到每个参数仅约1比特的水平76% similarUnverifiedSince 2024, 1-bit quantization (such as the BitNet series) has entered academic attention, compressing weights to ternary values {-1, 0, +1}, and it is currently still in the research stage69% similarUnverified微软研究院2023年提出的BitNet b1.58架构将所有权重限定为{-1, 0, +1}三个状态，理论上可将模型大小压缩至原来的1/16以下67% similarUnverified自回归推理的decode阶段是纯粹的内存带宽受限操作，将模型从FP16压缩到1-bit理论上可将token生成速度提升16倍65% similarUnverified1.58-bit refers to each weight occupying an average of log₂(3) ≈ 1.58 bits, because ternary weights (−1, 0, +1) have 3 possible states.63% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/572576API
curl https://kongchang.com/api/v1/knowledge/claims/572576MCP
get_claim(id=572576)