New Models from Meta, Kat Coder and Moonshot AI



AI never sleeps, and that’s especially true of the recent wave of launches from labs that aren’t always in the headlines. Hot on the heels of OpenAI’s three-model GPT-5.6 launch —and the return of Claude Fable—Meta, MoonshotAI and Kat Coder all just released models that are turning heads.
And all of these new models are live wherever you use Kilo: the CLI, JetBrains extension, VS Code extension, Cloud Agents and beyond.
New Kat Coder Tiers: Pro & Air
Kat Coder released two models this week for V2.5: Pro and Air. We’ve deployed both versions of KwaiPilot’s new architecture so you can route your tasks with precision:
Kat Coder Pro v2.5 (Free this week!): The powerhouse flagship. Built for complex, repository-level engineering challenges. Hand it a GitHub issue, and it will locate the files, implement the logic, and run tests until the issue is solved.
Kat Coder Air v2.5: The speed-optimized tier. Air brings the same core agentic planning and beautiful front-end aesthetic generation into a faster, highly cost-effective model for rapid everyday tasks.
Technical Highlights of the v2.5 Architecture
According to the KwaiPilot team’s newly released technical report on arxiv, building a world-class agentic model requires a complete rethink of training systems:
The AutoBuilder Engine: To train an agent to solve real-world problems, it needs a reliable sandbox. KwaiPilot developed AutoBuilder, an automated build-verification loop that reconstructs real repositories into isolated, executable environments. This pipeline boosted environment-construction success rates from 16.5% to 57.2%, yielding over 100,000 verified environments across 12 languages.
Process-Aware Trajectory Filtering: Instead of training the model purely on whether a test ultimately passed (which can reward lazy shortcuts), Kat Coder was trained using a process-aware pipeline. It scores the quality of the agent’s exploration, file localization, and recovery behavior, turning even near-miss failures in…