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ModelLLMsvb1.58

BitNet 1.58B

by Microsoft Research · open-source · Last verified 2026-03-17

BitNet b1.58 is Microsoft Research's revolutionary 1-bit large language model where every weight is ternary {-1, 0, +1}, reducing memory and energy consumption dramatically while matching full-precision models in performance. This architecture represents a paradigm shift for efficient AI inference, enabling LLMs to run on CPUs and highly constrained edge devices.

https://huggingface.co/microsoft/bitnet_b1_58-3B
C
CBelow Average
Adoption: CQuality: B+Freshness: ACitations: BEngagement: F

Specifications

License
MIT
Pricing
open-source
Capabilities
text-generation, cpu-inference, ultra-low-memory-inference, instruction-following
Integrations
BitNet.cpp, Hugging Face
Use Cases
CPU-only inference, ultra-low-power edge devices, IoT AI deployment, energy-efficient AI serving
API Available
Yes
Parameters
~3B
Context Window
4K
Modalities
text
Training Cutoff
2024
Tags
1-bit, efficient, microsoft, quantization, edge
Added
2026-03-17
Completeness
100%

Index Score

49.7
Adoption
48
Quality
71
Freshness
80
Citations
65
Engagement
0

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