Kimi K2.7 Code
moonshotai · moonshotai/kimi-k2.7-code
Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking
≈175k Chinese characters of context · Reads images · Step-by-step reasoning · Calls tools / agents · Structured JSON output · Open weights, self-hostable
Read a 200,000-Chinese-character book and write a 2,000-Chinese-character summary: about $0.30
An order-of-magnitude estimate at 1.5 tokens per Chinese character and the vendor's own rate — not a quote. Full method: the glossary on the AI Models page.
Specs
| Context | 262,144(≈175k Chinese characters) |
|---|---|
| Max output | 262,144 |
| Structured output | Yes |
| Open weights | Yes |
| Released | 2026-06-12 |
Source: models.dev snapshot 2026-08-29
Who serves it, at what price
| Provider | In /M | Out /M | Cache read /M |
|---|---|---|---|
| Moonshot AIfirst-party | $0.95 | $4 | $0.19 |
| AIHubMix | $0.95 | $3.9995 | $0.160835 |
| Alibaba Token Plan | Billed by plan | Billed by plan | $0 |
| Alibaba Token Plan (China) | Billed by plan | Billed by plan | $0 |
| Azure | $0.95 | $4 | $0.19 |
| Cortecs | $0.75 | $3.5 | $0.201 |
| CrofAI | $0.55 | $2.25 | $0.05 |
| GitHub Copilot | $0.95 | $4 | $0.19 |
| GreenPT | $0.9006 | $4.389 | $0.1881 |
| Charm Hyper | $1.03436 | $4.3552 | $0.206872 |
| DevPass (LLM Gateway) | $0.89 | $3.71 | $0.18 |
| Moonshot AI (China) | $0.95 | $4 | $0.19 |
| Neuralwatt | $0.95 | $4 | $0.095 |
| Ollama Cloud | — | — | — |
| OpenCode Zen | $0.95 | $4 | $0.19 |
| OpenCode Go | $0.95 | $4 | $0.19 |
| Requesty | $0.95 | $4 | $0.19 |
| routing.run | $0.275 | $1.1 | — |
| Volcengine Ark Coding Plan | Billed by plan | Billed by plan | $0 |
Rows tagged “first-party” are the model vendor's own pricing; untagged rows are resale channels and may differ.
When to choose it
This model is on our watch list but has no written assessment yet — we do not write what we cannot support. The specs and prices above still stand.
Leaderboard
Not yet on any leaderboard we track. That does not mean the model performs poorly — it means we have not taken this snapshot for it yet, and we do not publish a score we have not measured.