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Moonshot

Chat with Kimi K2.7 Code online

Moonshot's coding specialist — a trillion parameters pointed at agents that work across files, tools and the terminal.

Essayer Kimi K2.7 Code Voir les offres
Approuvé par 790,000+ utilisateurs

262.144K tokens

Contexte

131,072 tokens

Sortie maximale

Moyen

Vitesse

Ce pour quoi vous l'utiliserez

Agentic coding

Long runs across files, tools and terminal commands.

Large refactors

Multi-file changes that stay consistent to the end.

Debugging from evidence

Reads real error output and forms a hypothesis first.

Screenshot in, fix out

Paste a broken render and describe the fix.

Prompts to steal

Tuned to this model — click any line to copy.

À propos de Kimi K2.7 Code

Kimi K2.7 Code is the coding specialist in Moonshot AI's Kimi line, released on 12 June 2026. Where Kimi K3 is the generalist you ask about anything, K2.7 Code is the one pointed at software: a one-trillion-parameter mixture-of-experts model with about 32 billion parameters active per token, built for agents that operate across files, tools and terminal commands over an extended session rather than answering a single question.

Two things define it. The first is scope: a 262,144-token context window, which is enough to hold a substantial slice of a real codebase — several files, the configuration, the docs and a long agent transcript — without chunking tricks or aggressive summarisation. The second is restraint. Moonshot reports that K2.7 Code cuts reasoning token usage by roughly 30% against K2.6 while scoring about 21.8% higher on the lab's own Kimi Code Bench v2, which is the unusual combination of thinking less and getting more right.

Thinking is always on, so the model reasons before each response and each tool call rather than waiting to be asked. In practice that shows up as fewer wrong turns in the middle of a long refactor: it reads the error, forms a hypothesis, and checks it, instead of guessing and rerunning. It takes images as input too, so a screenshot of a broken render or a failing dashboard can go straight into the conversation.

The weights are open under a Modified MIT licence, which matters if you care about being able to self-host later or audit what you are building on. On NinjaChat it is included in every plan: pick it from the model list and keep a whole engineering task in one thread.

Comment utiliser Kimi K2.7 Code

De zéro à votre premier résultat en moins d'une minute.

01

Create a NinjaChat account and choose a plan

02

Open chat and pick Kimi K2.7 Code from the model list

03

Give it the files, the error output and the goal

04

Keep the whole task in one thread so its reasoning carries across turns

Conseils pour de meilleurs résultats

  • Paste stack traces verbatim; it debugs from evidence
  • Say which files it may change and which it may not
  • Ask for a plan before a big refactor, then let it execute
  • Switch to Kimi K3 when the question is not about code

Kimi K2.7 Code face aux alternatives

Comparaisons honnêtes — là où {model} excelle, et là où il ne le fait pas.

vs Kimi K3

Voir le modèle

+Tuned for code and long agent runs, and cheaper

–K3 is the stronger generalist for non-coding work

vs GPT-5.3 Codex

Voir le modèle

+Open weights and a lower price per token

–Codex has OpenAI's tooling and reasoning-effort controls

vs GLM 5.2

Voir le modèle

+More token-efficient over long coding sessions

–GLM 5.2 is broader across systems design

Questions fréquentes

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Kimi K2.7 Code, et 50 autres.

Un seul abonnement couvre tous les modèles de NinjaChat, Kimi K2.7 Code compris.

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D'autres modèles à explorer

Kimi K3

Le tout dernier modèle phare open-weight de Moonshot, avec vision native et contexte de 1M

→

GPT-5.3 Codex

OpenAI's agentic coding model for real software work

→

GLM 5.2

Le modèle phare de Z.ai pour le code, les agents et l'architecture logicielle

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