Published:
Today we are adding Kimi K2.7 Code to Chat-O’s Balanced tier. Released today by Moonshot AI, this model is a specialized member of the Kimi K2 family with one job: complete end-to-end programming tasks reliably, even when the work spans hundreds of thousands of tokens.
General-purpose models can write code. Coding specialists write code that works, across many files, with fewer dead ends and less hand-holding. The difference shows up most clearly in long tasks.
| Task Type | General Model | K2.7 Code |
|---|---|---|
| Single function from spec | Excellent | Excellent |
| Feature across 5+ files | Good, needs guidance | Excellent, self-directed |
| Bug fix with reproduction steps | Good | Excellent |
| Refactor with test updates | Fair | Excellent |
| Task completion rate (50K token projects) | ~70% | ~92% |
| Specification | Value |
|---|---|
| Context Window | 262,144 tokens |
| Modality | Text + Image (native multimodal) |
| Architecture | Mixture-of-Experts |
| Tier on Chat-O | Balanced |
| Release Date | June 12, 2026 |
| Best For | End-to-end programming, long-context code work |
We benchmarked K2.7 Code against three realistic scenarios that mirror actual development work.
We gave the model a ticket describing a new notification system for a Node.js backend, including database schema, API endpoints, and WebSocket push support. Total input context: about 40,000 tokens of existing code.
K2.7 Code produced the migration file, three new route handlers, the WebSocket server module, and integration tests in a single session. Every file referenced the others correctly. The tests passed on the first run after we fixed one typo in our own seed data.
A 30,000 line Django 3.2 project needed upgrading to Django 5.0. K2.7 Code identified every deprecated API usage, produced the updated code, and flagged three behavioral changes that required human review. It caught the MIDDLEWARE_CLASSES removal, the url() to path() migration, and a subtle change in timezone handling that would have broken our cron jobs.
We uploaded a Figma screenshot of a dashboard and asked for a React implementation. Thanks to native multimodal support, K2.7 Code produced a component tree with Tailwind classes that matched the design closely, including responsive breakpoints that were not visible in the screenshot but were inferable from the layout patterns.
| Model | Tier | Specialty | When to Use |
|---|---|---|---|
| Kimi K2.6 | Balanced | Multi-agent orchestration, UI generation | Agent workflows, UI from code |
| Kimi K2.7 Code | Balanced | End-to-end programming | Features, refactors, migrations |
| Kimi K3 | Power | 2.8T params, 1M context | Frontier reasoning, huge codebases |
If your task fits in 262K tokens and is primarily programming, K2.7 Code at Balanced tier pricing is the best value in the Kimi lineup. For truly massive repositories, step up to Kimi K3.
Z-AI’s GLM-5.1 targets similar long-horizon coding tasks but sits in the Power tier. K2.7 Code gives you comparable multi-file capability at Balanced tier prices, making it roughly 3x cheaper per session for equivalent work.
For a full comparison of coding-focused options, see our GLM lineup guide and Kimi lineup guide.
Kimi K2.7 Code is live in the model dropdown under Balanced models. New users get 1,000 free credits on signup, which covers several full feature-implementation sessions. No API keys, no configuration. Open a chat, paste your ticket, and watch it work.
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