Kimi K3.1 Pro and K3.1 Pro Highspeed

This page covers the models Kimi Code provides, how to switch models in each client, third-party tool setup, and common API issues.

Kimi Code currently offers six model IDs across K3.1 Pro (including K3.1 Pro Highspeed), K3 (including its 256K context variant), K2.8 Preview, and K2.7 Code Highspeed. Use a model ID to select a specific version in official clients or third-party tools. The table below compares specifications and plan requirements.

K3.1 Pro is now fully rolled out in Kimi Code—the first model of the new K3.1 series and our most capable 3T-class model to date, with a 1M context window and substantial improvements across coding, 3D creation, and financial research and modeling.

We're also releasing Kimi K3.1 Pro Highspeed, which—with identical model capabilities—delivers approximately 2–3× the speed of K3.1 Pro for more responsive interactions.

Different membership plans unlock different models, context windows, and speeds. Membership subscription →

If you don't have a client yet, download Desktop, the CLI, or the VS Code extension from the Kimi Code homepage.

The Kimi Code API supports OpenAI (Responses / Chat Completions) and Anthropic protocols. Tools that support the Responses API should use the native Responses format. Base URLs:

For detailed setup steps, see the corresponding tool guide:

Claude CodeAnthropic's command-line coding assistantOpenCodeA terminal-based coding agentCodexOpenAI's coding agent

Effort mapping and routing rules ​

K3.1 Pro models, the K3 series, and K2.8 Preview support low / high / max thinking effort levels. Third-party tool values are mapped as follows. K2.7 Code Highspeed does not support adjustable thinking effort.

Changing thinking effort also invalidates the context cache. Keep the same effort within a session when possible. If you need to change it, start a new session to avoid repeated prefills and additional token usage.

A valid model ID only identifies the model. Whether the request succeeds also depends on account permissions, thinking mode, and context limits. Check the error message:

Keep the same model and thinking effort within a session instead of switching back and forth. Switching models or thinking effort invalidates the existing context cache, requiring a new prefill and increasing token usage. Reasoning chains from different models can also affect each other.

Switching from K3 (1M) to K3-256k: if the current session's context already exceeds 256k, some coding tools (such as Kimi Code CLI and Claude Code) will perform a compact on the tool side. Recommendations:

Switching from K3-256k to K3 (1M): if k3-256k is close to the 256k limit and you don't want compact to lose information, you can switch directly to 1M. The current version switching from 256k to 1M does not affect the cache.