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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.

Coba Kimi K2.7 Code Lihat paket
Dipercaya 790,000+ pengguna

262.144K tokens

Konteks

131,072 tokens

Output maks

Sedang

Kecepatan

Untuk apa Anda akan menggunakannya

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.

Tentang 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.

Cara menggunakan Kimi K2.7 Code

Dari nol ke hasil pertama Anda dalam waktu kurang dari satu menit.

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

Tips untuk hasil yang lebih baik

  • 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 vs alternatif lainnya

Perbandingan jujur — di mana {model} unggul, dan di mana tidak.

vs Kimi K3

Lihat model

+Tuned for code and long agent runs, and cheaper

–K3 is the stronger generalist for non-coding work

vs GPT-5.3 Codex

Lihat model

+Open weights and a lower price per token

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

vs GLM 5.2

Lihat model

+More token-efficient over long coding sessions

–GLM 5.2 is broader across systems design

Pertanyaan yang sering diajukan

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Kimi K2.7 Code, dan 50 lainnya.

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Model lain untuk dijelajahi

Kimi K3

Model unggulan open-weight terbaru Moonshot dengan vision native dan konteks 1M

→

GPT-5.3 Codex

OpenAI's agentic coding model for real software work

→

GLM 5.2

Model andalan Z.ai untuk coding, agen, dan pekerjaan sistem

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