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Kimi K2.7 Code

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What is Laguna M.1?

Laguna M.1 is recognized as Poolside's premier model for agentic coding, meticulously designed in-house to optimize software development processes. This sophisticated model incorporates 225 billion parameters and employs a Mixture of Experts architecture with 23 billion parameters activated, all trained on a colossal dataset of 30 trillion tokens using a network of 6,144 NVIDIA H200 GPUs. Poolside committed to developing Laguna M.1 from the ground up, utilizing proprietary data, a specialized training codebase, and an asynchronous on-policy reinforcement learning strategy within its agent framework, all specifically oriented towards agentic coding applications. The model's architecture is crafted to deliver top-tier performance within Poolside's coding agent, empowering it to adeptly reason through programming tasks, engage with an array of tools, modify code, run tests, and support extensive autonomous development sessions. Tailored for developers and teams facing complex coding obstacles, Laguna M.1 boasts enhanced capabilities in reasoning, understanding architecture, managing terminal actions, and executing multi-step processes, far exceeding the abilities of lighter models. Overall, its comprehensive feature set establishes it as an indispensable tool for professionals immersed in high-stakes software projects, making it a vital component in the landscape of agentic coding solutions.

What is Kimi K2.7 Code?

Kimi K2.7 Code is an open-source agentic coding model from Moonshot AI designed for developers, engineering teams, and AI coding workflows that require long-context understanding and multi-step execution. It is built for real-world software engineering tasks, including code generation, code review, debugging, repository navigation, tool use, and long-horizon development work. The model is described by Moonshot AI as a coding-focused agentic model with stronger performance on complex coding tasks than earlier Kimi K2 releases. Kimi K2.7 Code supports a 256K context window, allowing it to process large codebases, technical requirements, logs, documentation, and multi-file development context in a single workflow. It is available through Kimi Code, which provides developer-oriented tools for using the model in coding tasks. The model can also be accessed through Moonshot’s API platform, where Kimi K2.7 Code and Kimi K2.7 Code Highspeed are offered alongside earlier Kimi models. For developers who want more control, Kimi K2.7 Code is listed on Hugging Face with deployment support for inference engines such as vLLM, SGLang, and KTransformers. It uses OpenAI- and Anthropic-compatible API options, helping teams connect it to existing applications, coding tools, and agent systems more easily. Third-party model listings describe it as using a 1T-parameter mixture-of-experts architecture with 32B active parameters, native INT4 quantization, and reduced thinking-token usage compared with Kimi K2.6. The model is designed to improve efficiency by using fewer reasoning tokens while still supporting demanding programming workflows. Kimi K2.7 Code is a strong fit for developers who want an open, long-context, tool-friendly AI model for software engineering automation and AI-assisted development.