Moonshot AI model releases

Moonshot AI's mid-tier coding and agentic model, released Sep 11 2026 and positioned between the flagship Kimi K3 and the older Kimi K2.7 Code. Moonshot describes its coding and agent performance as close to K3 with significantly more efficient "thinking," and brings the K3-series thinking controls — adjustable reasoning effort set to low, high, or max, with max as the default. Multimodal input (text, images, and video) with text output, and a 1M-token context window made available across all Kimi membership tiers rather than gated to upper plans as it was when K3 first opened 1M context. Served through Kimi Code under the model id kimi-for-coding, so existing clients pick it up without config changes. Proprietary and preview-status at launch; parameter count and architecture are undisclosed for this specific checkpoint, though it sits within Moonshot's MoE Kimi K2 line. Benchmark and efficiency figures are vendor-reported and unverified by an independent harness at launch.

Moonshot's flagship open-weight agentic model and the largest open model released to date: a 2.8T-parameter MoE (896 experts, 16 active per token) using Kimi Delta Attention and Attention Residuals, with native multimodal input and a 1M-token context. Launched via API on Jul 16, 2026 at $3/$15 per Mtok (cached input $0.30); full open weights published to Hugging Face on Jul 26, 2026 — a day ahead of the announced Jul 27 target — under a Modified MIT license, making it freely downloadable and self-hostable.

Moonshot's open coding-focused agentic model built on K2.6, with native vision/video input, forced thinking mode, and stronger long-horizon software-engineering performance.

Moonshot's open native multimodal agentic model for long-horizon coding, visual interface generation, and autonomous tool orchestration.

Open multimodal Kimi model that adds native visual agentic intelligence, instant and thinking modes, and agent-swarm workflows on top of the K2 base.

Open K2 reasoning-agent variant that interleaves step-by-step thinking with tool calls and supports stable 200-300 step tool-use trajectories.

MIT-licensed hybrid linear-attention model using Kimi Delta Attention, built for million-token contexts with much lower KV-cache usage.

September 2025 K2 update with stronger agentic coding, better frontend generation, and a doubled 256K context window.

Original open K2 post-trained model: a 1T-parameter MoE optimized for coding, reasoning, and tool-using agentic workflows.

Updated MIT-licensed Kimi-VL reasoning model with better multimodal reasoning, video understanding, high-resolution perception, and lower thinking-token use.

MIT-licensed coding LLM trained with repository-level reinforcement learning for software issue resolution.

Open audio foundation model for audio understanding, generation, speech recognition, audio QA, captioning, and speech conversation.

Efficient MIT-licensed vision-language MoE for OCR, image/video understanding, long documents, and OS-style agent tasks.

MIT-licensed 16B/3B-active MoE trained with Moonshot's scalable Muon optimizer experiments.

Moonshot's multimodal reinforcement-learning reasoning model, reported as matching OpenAI o1 on math, coding, and multimodal reasoning.

Long-context Kimi upgrade advertised with support for million-character document and conversation contexts.

Moonshot's first Kimi assistant release, establishing the long-context product line before the open Kimi model cards.