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Kimi K2.5: Open-sourced Coding Model

Updated 6 February 2026

Moonshot AI has introduced the most powerful open-source model, so far, called Kimi K2.5.

This is a major enhancement that alters the way artifical intelligence perceives, thinks, codes, and performs activities in the real-life scenarios.

K2.5 is an extension of Kimi K2, and also includes a lot of pre-training on about 15 trillion mixed text with visual tokens.

It is a multimodal model that is native, thus vision and text are learned simultaneously.

With such scale, the common trade-off no longer exists: strong vision does not negatively affect reasoning or the quality of code.

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Kimi is available through Kimi.com, Kimi App, API and Kimi Code. The Kimi App currently has four modes:

  • K2.5 Instant
  • K2.5 Thinking
  • K2.5 Agent
  • K2.5 Agent Swarm (Beta)

The actual advantage is not the increase in score only but the quicker and more accurate completion of complicated tasks.

Coding with visual understanding

The most powerful open-source coding model at the moment, particularly in the front-end work, is K2.5.

Even a simple chat can become a full interface with layouts and animations.

The the distinctive feature of K2.5 is that it is not based on text alone.

It is capable of reasoning directly on the pictures and videos and the hurdle to the declaration of intent is reduced significantly.

Demand what you desire rather than write about it step by step

K2.5 can:

  • Turn images or videos to working front-end code.
  • Visual debugging – Visual inspection of its own output.
  • Work with visual problems by solving them with code and reasoning.

For example, K2.5 solves a maze by turning the image into a grid and finding the shortest path.

This is autonomous visual thinking, not a pipeline, each step is decided independently by the model.

These are skills acquired through massive joint training by vision and text. Vision at this scale is also enhanced, so is reasoning and coding.

Kimi K2.5 : Built for real coding

K2.5 is not only a demonstration but it is a good professional in actual engineering work.

It is tested on Kimi Code Bench, which covers building, fixing, testing, and coding in many languages.

Through these activities, K2.5 is improving steadily compared to K2 especially in terms of end-to-end workflow.

To make this easy, Moonshot launched Kimi Code, a tool that runs locally and works with IDEs like VS Code, Cursor, and Zed.

Kimi Code:

  • Is open source
  • Accepts picture and video input.
  • Recognizes available tools and MCPs automatically.

This makes K2.5 an everyday coding partner, as opposed to a chat model.

Agent Swarm: Parallel Scaling Over Vertical Scaling

The greatest contribution in K2.5 is Agent Swarm. Rather than using one agent, K2.5 can generate and synchronize up to 100 sub-agents, and run up to 1,500 tool calls at the same time.

This is 4.5x faster than a single-agent implementation, and includes no pre-existing roles or designed workflows.

Parallel-Agent Reinforcement Learning (PARL) is used to train agent Swarm.

One of the key planners gets to know how to divide tasks into parallel sub tasks and perform them simultaneously.

Rewards promote parallel performance at an early stage of training. Further on, the emphasis is put on quality of tasks in general to prevent senseless parallelism.

In order to measure performance, critical steps are used, a latency-based metric, in order to guarantee actual speedups.

Parallelism can only assist in case it reduces the slowest path of execution.

Why Agent Swarm Matters

In internal evaluations, Agent Swarm provides:

  • 80 per cent shorter end to end runtime.
  • 3-4.5 times fewer steps on difficult tasks
  • Takes Critical Responsibility: – 3-4.5 fewer steps on complex tasks
  • Improved performance on search intensive and long horizon workloads.

For example, when asked, K2.5 can create many agents to find results and combine them into a spreadsheet on its own

Kimi K2.5 Agents scale of Office Productivity

kimi k2.5 img

Image Source : [email protected]

Even agentic intelligence is introduced into daily office life through K2.5. It is able to think through massive, thick input and produce refined output in the middle of conversation.

It supports:

  • Annotated word documents.
  • Financial models with Pivot Tables.
  • PDFs with LaTeX equations
  • 10,000-word papers or 100-page documents.
  • K2.5 works much better than K2 Thinking on office tasks and agent work.

Conclusion

K2.5 does not concern itself with winning one benchmark.

It is an open-source system that combines coding, vision, and smart agents for real work.

For developers and researchers, Kimi K2.5 is a big step toward AI that works in real life.

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