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Prompts and workflows

Kimi K2.7 Code · configuration

Kimi K2.7 Code: Official Claude Code Integration & Multi-Tier Model Mapping

The official Claude Code guide focuses on endpoint mapping, model aliases, and a controlled coding session.

Source not verifiedClaude Code, a Moonshot-compatible endpoint, model mapping, and an isolated repository.

Prerequisites and inputs

  • Task goal and source material
  • Client or API
  • Output format and acceptance checks

Prerequisites

Claude Code, a Moonshot-compatible endpoint, model mapping, and an isolated repository.

Task steps

Pin the model version, inputs, and tool permissions; save returns, errors, and acceptance evidence after each round.

Task result

Deliver the artifact for “Kimi K2.7 Code: Official Claude Code Integration & Multi-Tier Model Mapping” and list assumptions not confirmed by the source or inputs.

Output and acceptance

Run the actual checks and record format, critical paths, tool state, and failed items.

Failure correction

Reproduce the smallest failing case, narrow the input, or fix configuration; do not treat model self-report as evidence.

Source and boundary

The official Claude Code guide focuses on endpoint mapping, model aliases, and a controlled coding session.

Read the source research notes

One-Line Summary

Forwarding Claude Code requests to Kimi's Anthropic-compatible endpoint requires explicitly keeping Thinking enabled (Tab key), setting the auto-compact window to 256K (262144), and fully mapping all Opus/Sonnet/Haiku/Fable/Subagent tier aliases.

Applicable Scenarios

  • Suitable tasks: Repository-level coding, multi-file refactoring, test execution, and subagent orchestration in Claude Code CLI.

  • Unsuitable tasks: Zero-thinking fast generation, single prompt dumps exceeding 256K context, partial configurations missing Haiku/Subagent variables.

  • Applicable model versions: kimi-k2.7-code (Standard), kimi-k2.7-code-highspeed (~180–260 tokens/s).

  • Applicable clients/APIs: @anthropic-ai/claude-code CLI, Kimi Anthropic-compatible API endpoint (https://api.moonshot.ai/anthropic).

  • Recommended inference parameters: CLAUDE_CODE_EFFORT_LEVEL="max", CLAUDE_CODE_AUTO_COMPACT_WINDOW="262144", Thinking enabled.

Directly Usable Content

Option 1: Terminal Environment Variables (Current Session)

macOS / Linux (bash/zsh)

export ANTHROPIC_BASE_URL="https://api.moonshot.ai/anthropic"
export ANTHROPIC_AUTH_TOKEN="YOUR_MOONSHOT_API_KEY"
export ANTHROPIC_MODEL="kimi-k2.7-code"
export ANTHROPIC_DEFAULT_OPUS_MODEL="kimi-k2.7-code"
export ANTHROPIC_DEFAULT_SONNET_MODEL="kimi-k2.7-code"
export ANTHROPIC_DEFAULT_HAIKU_MODEL="kimi-k2.7-code"
export ANTHROPIC_DEFAULT_FABLE_MODEL="kimi-k2.7-code"
export CLAUDE_CODE_SUBAGENT_MODEL="kimi-k2.7-code"
export CLAUDE_CODE_AUTO_COMPACT_WINDOW="262144"
export CLAUDE_CODE_EFFORT_LEVEL="max"
claude

Windows (PowerShell)

$env:ANTHROPIC_BASE_URL="https://api.moonshot.ai/anthropic";
$env:ANTHROPIC_AUTH_TOKEN="YOUR_MOONSHOT_API_KEY";
$env:ANTHROPIC_MODEL="kimi-k2.7-code";
$env:ANTHROPIC_DEFAULT_OPUS_MODEL="kimi-k2.7-code";
$env:ANTHROPIC_DEFAULT_SONNET_MODEL="kimi-k2.7-code";
$env:ANTHROPIC_DEFAULT_HAIKU_MODEL="kimi-k2.7-code";
$env:ANTHROPIC_DEFAULT_FABLE_MODEL="kimi-k2.7-code";
$env:CLAUDE_CODE_SUBAGENT_MODEL="kimi-k2.7-code";
$env:CLAUDE_CODE_AUTO_COMPACT_WINDOW="262144";
$env:CLAUDE_CODE_EFFORT_LEVEL="max";
claude

Option 2: Persistent Configuration (~/.claude/settings.json)

{
  "env": {
    "ANTHROPIC_BASE_URL": "https://api.moonshot.ai/anthropic",
    "ANTHROPIC_AUTH_TOKEN": "YOUR_MOONSHOT_API_KEY",
    "ANTHROPIC_MODEL": "kimi-k2.7-code",
    "ANTHROPIC_DEFAULT_OPUS_MODEL": "kimi-k2.7-code",
    "ANTHROPIC_DEFAULT_SONNET_MODEL": "kimi-k2.7-code",
    "ANTHROPIC_DEFAULT_HAIKU_MODEL": "kimi-k2.7-code",
    "ANTHROPIC_DEFAULT_FABLE_MODEL": "kimi-k2.7-code",
    "CLAUDE_CODE_SUBAGENT_MODEL": "kimi-k2.7-code",
    "CLAUDE_CODE_AUTO_COMPACT_WINDOW": "262144",
    "CLAUDE_CODE_EFFORT_LEVEL": "max"
  }
}

Testing / Workflow Steps

  1. Install Claude Code: npm install -g @anthropic-ai/claude-code.

  2. Obtain an API Key from Kimi API Platform (platform.kimi.ai).

  3. Set environment variables or update ~/.claude/settings.json.

  4. Run claude and execute /status to verify:

    • Base URL displays https://api.moonshot.ai/anthropic

    • Model displays kimi-k2.7-code

  5. Press Tab in Claude Code to ensure the "Thinking on" indicator is active.

  6. Submit a test instruction (e.g. summarize directory structure and package.json) to confirm tool execution.

Raw Evidence & Data

  • Multi-tier model fallback: Claude Code uses Haiku for background summaries and Opus/Sonnet for complex tasks. Omitting tier variables causes silent 404/auth failures.

  • Compaction window matching: K2.7 Code has a 256K window (262144). Setting 1M causes context overflow errors; setting too low causes premature context loss.

  • Thinking requirement: kimi-k2.7-code rejects non-thinking requests with HTTP 400 (invalid thinking: only type=enabled is allowed).

Boundaries & Constraints

  • Requires Kimi's Anthropic compatibility endpoint; unofficial wrappers must support reasoning token propagation.

  • /model menu in Claude Code is hardcoded and will not list Kimi aliases; verify via /status.

Source and dates

Kimi API Platform Documentation · Source date: Not disclosed · Edited: 2026-09-20

Read the original source
Variable checklist

No required variables

Related prompts

Kimi K2.7 Code: Official Multimodal Video Tool Calling & Agent LoopKimi K2.7 Code: Official GitHub Copilot Integration & Enterprise Policy SetupKimi K2.7 Code: Official Integration and Long-Horizon Coding Prompt WorkflowUnsiloed Benchmark: Full FastAPI Project Generation Prompt & Architectural Standard

Related reviews

Kimi K2.7 Code: Official Hugging Face Model Specifications and Full Benchmark DataUnsiloed Benchmark: Kimi K2.7 Code vs GLM 5.2 Controlled Benchmark on Real-World Code Generation and Large Repository AnalysisDevin Team: FrontierCode Extended Benchmark and Long-Horizon Engineering PerformanceOpenCode Community: Real-World Agentic Coding Cost & Tool Loop Efficiency Comparison

Read the full analysis

Overview · English

Kimi K2.7 Code: What It Is, What It Costs, and Who It Fits

A sourced Kimi K2.7 Code overview: the $4/M output anchor, 256K multimodal coding model, K2.6/K3 boundary, access routes and pilot risks.

Kimi K2.7 Code

Use Kimi K2.7 Code in Tabbit

Run this guide in the environment listed above. Downloading does not transfer the template or establish model availability for your account.