Really cool. @atomic_chat_hq 's 1-bit Kimi K3 quant shrinks the 2.8T model to 590GB (-62%)
Rohan Paul Twitter · Rohan Paul (@rohanpaul_ai) · 2026-07-31
Atomic Chat's 1-bit quantization of Kimi K3 reduces the 2.8 trillion parameter model to 590GB—a 62% size reduction—while retaining 78.7% of original quality and full 1M context support, demonstrated running locally on 4x NVIDIA B200 GPUs.
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Extraction
Topics: model-quantizationkimi-k31-bit-llmlocal-inferencellm-efficiency
Claims
- 1-bit quantization of Kimi K3 compresses the 2.8T parameter model from its original size to 590GB, a 62% reduction.
- The 1-bit quantized model retains 78.7% agreement with the original model while preserving the full 1M token context window.
- Increasing to 2.1-bit quantization raises quality agreement to 87.2% at 769GB, while 3.4-bit adds 428GB for only 0.5 percentage points of additional quality.
- In a practical HTML 3D physics test, the local 1-bit K3 was the only model among four tested (including Kimi K3 API, Opus 5, and GPT 5.6) to build a working winch mechanism.
- Running the 1-bit model locally on 4x B200 GPUs costs $0 in API fees versus $0.30–$0.77 for cloud alternatives.
Key quotes
1-bit Kimi K3 performs at Opus 5 level on 3D physics!
All four got the physics right. But only Kimi made a working winch. The drum turns and the chain drags the flat car off the pad.
And you can run a model at this level on your own box now. That still feels insane to us.