Kimi Developers

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

Kimi K3 has everyone’s attention. On July 30, hear @Kimi_Moonshot's Feihu Tang explain the architecture and decisions behind it. He joins Jue Wang and Zain Hasan from Together AI for a deep dive into long-running agents and production inference.

With Kimi K3 Day-0 on vLLM: Open Frontier Intelligence for Everyone 🚀 At 2.8 trillion parameters, Moonshot AI's Kimi K3 is one of the most powerful open-weight models ever released. Starting today, you can serve it on vLLM the moment the weights are public. What K3 brings: 🧠 2.8T-parameter Mixture-of-Experts (16 of 896 experts active per token) 📚 1M-token context window 🛠️ Native multimodal understanding, including vision ⚡ Kimi Delta Attention: a hybrid of linear and full attention that makes million-token context affordable Huge thank you to @Kimi_Moonshot AI for the model release and partnership, @inferact for leading the vLLM optimizations, and to our partners at @nvidia, @AMD, and the broader vLLM community. 1/6

SGLang day-0 speed on Kimi K3: 423 tok/s (measured on gsm8k), plus RL support ready in Miles @radixark! How the largest open-source model runs this fast: we natively implemented and deeply optimized K3’s new architecture with fused KDA decode kernels, DP attention, DSpark, PD disagg, and KDA-aware prefix caching. We've passed Kimi Vendor Verifier and are ready for production! Thanks to @Kimi_Moonshot, @nvidia, @AMD, @KVCache_AI, @modal, and @baseten for building this with us, and to @googlecloud, @nebiustf, @fal, @digitalocean, @runpod, @DeepInfra and @gmi_cloud for serving K3 on SGLang. Blog, cookbook, benchmarks in the comments. P.S. This demo video? Kimi K3 made it itself. Play the game 👇

Kimi K3 is now supported in TokenSpeed. We worked closely with the @Kimi_Moonshot team to bring Day 0 support to both NVIDIA Blackwell ((G)B200/(G)B300) and AMD Instinct (MI350X/MI355X) in just one week. ✅ Prefix caching ✅ Speculative decoding ✅ Disaggregated serving ✅ CUDA Graph decode We also share how we optimized KDA, Gated MLA, Stable LatentMoE, AttnRes, and our unified Flat KV architecture. Blog ↓ lightseek.org/blog/tokenspee…