Kimi K3.1 Pro is Moonshot AI's flagship open-weight multimodal reasoning model and the first in the K3.1 series, a post-trained version of Kimi K3 with substantially more post-training compute, built on the same Kimi Delta Attention and Attention Residuals architecture (K3: 2.8T total, 104B active parameters; Moonshot calls K3.1 Pro 3T-class). It has a 1M-token context window with flat pricing across the full window, accepts text and images, and returns text, with always-on reasoning (effort: low, high, or max; default max) that cannot be turned off. It is designed for long-horizon coding, agentic and tool-using workflows, and complex knowledge work, and is exposed through an OpenAI-compatible chat completions API. Moonshot has said full weights will be released by November 4, 2026.
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<FASTROUTER_API_KEY> with your key · Get your key →Installmoonshotai/kimi-k3Kimi K3 is Moonshot AI’s 2.8-trillion-parameter flagship multimodal reasoning model with a 1M-token context window, designed for long-horizon coding, complex knowledge work, visual reasoning, and tool-using workflows. It uses Kimi Delta Attention and Attention Residuals to support efficient million-token contexts and always runs in high-effort reasoning mode. The model is exposed via an OpenAI-compatible chat completions API.
moonshotai/kimi-k2.7-codeKimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built for reliable end-to-end programming tasks over long contexts. It supports text and image input, always operates in thinking mode, and is designed for long-horizon coding, agentic task decomposition, tool use, and multi-turn workflows.
moonshotai/kimi-k2.6Moonshot AI's Kimi-K2.6 is a frontier-scale, open-source Mixture-of-Experts (MoE) multimodal model with 1 trillion total parameters (32B active), a 256K-262K token context window, and native support for text, image, and video inputs, excelling in long-horizon coding, agentic workflows, multi-agent orchestration, and complex software engineering.
moonshotai/kimi-k2.5MoonshotAI's Kimi-K2.5 is a cutting-edge open-source multimodal large language model series from MoonshotAI, featuring a massive Mixture-of-Experts (MoE) architecture with 1 trillion total parameters—yet only 32 billion activated per token for highly efficient inference and low computational costs. It boasts 61 transformer layers, 64 attention heads, a 256K context window enabled by advanced MLA attention mechanisms, and SwiGLU activations, paired with a MoonViT vision encoder for native handling of images, videos, and cross-modal tasks like visual reasoning, UI mockup-to-code generation (e.g., React from screenshots), and agentic workflows.
Model scores sourced from ArtificialAnalysis