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Kimi K3: a 2.8 trillion-parameter, native-multimodal model with a 1,000,000-token…

2026-07-16 · 19:28 UTC ·@0xDevShah ·0 min read

Brief

Kimi K3 is a 2.8T-parameter, native-multimodal model with a 1,000,000-token context window that targets long-horizon agentic coding and self-evolving workflows. Kimi claims Delta Attention yields up to 6.3× faster decoding at million-token context sizes and Attention Residuals boost training efficiency by ~25% for <2% extra cost; weights to be open by July 27, 2026.

Why it matters

Kimi K3: a 2.8 trillion-parameter, native-multimodal model with a 1,000,000-token context window announced by Kimi.ai (@Kimi_Moonshot).

Key details

  • Kimi Delta Attention claims up to 6.3x faster decoding at million-token contexts; Attention Residuals claim ~25% higher training efficiency for under 2% additional cost.
  • Kimi K3 is live on kimi.com, Kimi Work, Kimi Code, and the Kimi API (platform.kimi.ai); weights promised open by July 27, 2026 (tech blog: kimi.com/blog/kimi-k3).
Source evidence

we are so back or it is so over depending entirely on your compute budget

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