# Kimi K2.7 Code

> Coding specialist. +21.8% Kimi Code Bench vs K2.6, ~30% fewer reasoning tokens. Always-thinking. 262K context.

Human version: https://kymaapi.com/models/kimi-k2.7-code
Live JSON: `GET https://kymaapi.com/v1/models` (no auth required)

## Facts

- **Model ID**: `kimi-k2.7-code` — pass this as `model` in the request body
- **Creator**: Moonshot AI
- **Released**: 2026-06-12
- **Context window**: 262K tokens
- **Max output**: 16K tokens per response — a hard ceiling, not a default
- **Price**: $1.009 in / $4.774 out per 1M
- **Capabilities**: tools, vision, reasoning

## Call it

```bash
curl https://kymaapi.com/v1/chat/completions \
  -H "Authorization: Bearer $KYMA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "kimi-k2.7-code", "messages": [{"role": "user", "content": "Hello"}]}'
```

## Positioning

Moonshot's coding-specialist build of Kimi K2 on Kyma — a trillion-parameter mixture-of-experts model tuned for end-to-end programming, with a 262K-token context window and an always-on thinking mode.

## About

Kimi K2.7 Code is Moonshot AI's June 2026 coding-focused release in the Kimi K2 family, a 1T-parameter mixture-of-experts model released under a modified MIT license. Where the general K2.6 spreads across agentic, vision, and reasoning work, K2.7 Code is built to complete programming tasks reliably over long contexts, and it always operates in a thinking mode that preserves full reasoning across multi-turn conversations.

Against K2.6 it posts +21.8% on Kimi Code Bench v2 and +31.5% on MLS Bench Lite while using roughly 30% fewer reasoning tokens — so it tends to reach a correct answer with less generated text, which lowers the effective cost on output-heavy coding loops. It accepts both text and image input and supports function calling and structured outputs, so it slots into existing agent frameworks.

On Kyma it routes with automatic failover across multiple serving paths, bills exact per-request cost in usage.cost, and is reachable with the same OpenAI-compatible key as every other model. The 262K-token context window holds a substantial codebase plus the agent's working state, and the always-thinking design suits multi-step tasks over one-shot replies.

## Use cases

- **End-to-end coding tasks** — Its core design target — completing programming work reliably across long contexts rather than answering isolated snippets.
- **Agentic programming loops** — Function calling plus structured outputs keep read-edit-test-iterate agent cycles parseable and on schema.
- **Cost-sensitive coding** — Roughly 30% fewer reasoning tokens than K2.6 means lower output spend on long, output-heavy sessions.
- **Multimodal code context** — Text-plus-image input lets you pass screenshots, diagrams, or UI mockups alongside the code prompt.

## Not ideal for

Quick interactive chat where its always-on thinking mode adds latency, or general non-coding agentic work — for that, Kimi K2.6 is the better fit.

## See also

- All models: https://kymaapi.com/models.md
- Pricing: https://kymaapi.com/pricing.md
- Other models by Moonshot AI: https://kymaapi.com/models?q=Moonshot%20AI