Daniel Han
@danielhanchen
Building @UnslothAI • Making open-source LLMs faster, better & more accessible • YC S24 • ex-NVIDIA ML
加入 April 2016
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We quantized GLM-5.3 to dynamic 1-bit (217GB) vs BF16 (1.5TB) and it retains ~76% top-1% accuracy whilst being 83%
We did a small basic snake game in Unsloth Desktop using the UD 1-bit and it worked well!
zai is on a roll with GLM-5.3-Flash and now GLM-5.3!
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GLM-5.3 can now be run locally!
The 2-bit model retains ~81% accuracy after we shrunk it from 1.51TB to 239GB (-83% size).
Run on a 256GB Mac or RAM/VRAM setups.
GLM-5.3 is the strongest open model to date.
Guide:
GGUF:
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