@UnslothAI: a 1-bit compressed Kimi K3 retains ~78.9% accuracy after shrinking…

Brief

Kimi K3 is presented as a 2.8 trillion-parameter, native multimodal model with a 1,000,000-token context; UnslothAI released a 1-bit compressed variant that reportedly keeps ~78.9% accuracy after shrinking from 1.56 TB to 594 GB and can run on a Mac Studio with 128 GB RAM. Kimi.ai touts Kimi Delta Attention (up to 6.3× faster decoding at million-token contexts) and Attention Residuals (~25% training efficiency gain at <2% extra cost), with open weights slated for July 27, 2026.

Key details

Kimi.ai claims Kimi K3 is a 2.8 trillion-parameter, native multimodal model with a 1,000,000-token context; Kimi Delta Attention enables up to 6.3× faster decoding at million-token contexts and Attention Residuals deliver ~25% higher training efficiency at <2% additional cost

Kimi K3 is promoted as the strongest open model to date, announced live on Kimi.com, Kimi Work, Kimi Code and the Kimi API, with open weights promised by July 27, 2026

Kimi K3 can now be run locally! ✨

The 1-bit model retains ~78.9% accuracy after we shrunk it from 1.56TB to 594GB (-62% size).

Run on a Mac Studio + 128GB RAM device.

Kimi K3 is the strongest open model to date.

Guide: unsloth.ai/docs/models/kimi-…
GGUF: huggingface.co/unsloth/Kimi-…

Kimi.ai (@Kimi_Moonshot)

Introducing Kimi K3: Open Frontier Intelligence

🔹 2.8 Trillion Parameters, 1 Million Context, Native Multimodal
🔹 Kimi Delta Attention enables up to 6.3x faster decoding in million-token contexts
🔹 Attention Residuals deliver ~25% higher training efficiency at <2% additional cost
🔹 Built for long-horizon agentic coding and self-evolving workflows

Kimi K3 is now live on on Kimi.com, Kimi Work, Kimi Code, and the Kimi API.
Open Weights by July 27, 2026.

🔗 API: platform.kimi.ai
🔗 Tech blog: kimi.com/blog/kimi-k3

— https://nitter.net/Kimi_Moonshot/status/2077830229968683203#m

Brief

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