Providers and Models

Kimi Code CLI supports multiple LLM platforms, which can be configured via configuration files or the /login command.

Platform selection

The easiest way to configure is to run the /login command (alias /setup) in shell mode and follow the wizard to select platform and model:

1. Select an API platform
2. Enter your API key
3. Select a model from the available list

After configuration, Kimi Code CLI will automatically save settings to ~/.kimi/config.toml and reload.

/login currently supports the following platforms:

Platform	Description
Kimi Code	Kimi Code platform, supports search and fetch services
Moonshot AI Open Platform (moonshot.cn)	China region API endpoint
Moonshot AI Open Platform (moonshot.ai)	Global region API endpoint

For other platforms, please manually edit the configuration file.

Provider types

The type field in providers configuration specifies the API provider type. Different types use different API protocols and client implementations.

Type	Description
kimi	Kimi API
openai_legacy	OpenAI Chat Completions API
openai_responses	OpenAI Responses API
anthropic	Anthropic Claude API
gemini	Google Gemini API
vertexai	Google Vertex AI

kimi

For connecting to Kimi API, including Kimi Code and Moonshot AI Open Platform.

[providers.kimi-for-coding]
type = "kimi"
base_url = "https://api.kimi.com/coding/v1"
api_key = "sk-xxx"

openai_legacy

For platforms compatible with OpenAI Chat Completions API, including the official OpenAI API and various compatible services.

[providers.openai]
type = "openai_legacy"
base_url = "https://api.openai.com/v1"
api_key = "sk-xxx"

openai_responses

For OpenAI Responses API (newer API format).

[providers.openai-responses]
type = "openai_responses"
base_url = "https://api.openai.com/v1"
api_key = "sk-xxx"

anthropic

For connecting to Anthropic Claude API.

[providers.anthropic]
type = "anthropic"
base_url = "https://api.anthropic.com"
api_key = "sk-ant-xxx"

gemini

For connecting to Google Gemini API.

[providers.gemini]
type = "gemini"
base_url = "https://generativelanguage.googleapis.com"
api_key = "xxx"

vertexai

For connecting to Google Vertex AI. Requires setting necessary environment variables via the env field.

[providers.vertexai]
type = "vertexai"
base_url = "https://xxx-aiplatform.googleapis.com"
api_key = ""
env = { GOOGLE_CLOUD_PROJECT = "your-project-id" }

Model capabilities

The capabilities field in model configuration declares the capabilities supported by the model. This affects feature availability in Kimi Code CLI.

Capability	Description
thinking	Supports thinking mode (deep reasoning), can be toggled
always_thinking	Always uses thinking mode (cannot be disabled)
image_in	Supports image input
video_in	Supports video input

[models.gemini-3-pro-preview]
provider = "gemini"
model = "gemini-3-pro-preview"
max_context_size = 262144
capabilities = ["thinking", "image_in"]

thinking

Declares that the model supports thinking mode. When enabled, the model performs deeper reasoning before answering, suitable for complex problems. In shell mode, you can use the /model command to switch models and thinking mode, or control it at startup with --thinking / --no-thinking flags.

always_thinking

Indicates the model always uses thinking mode and cannot be disabled. For example, models with "thinking" in their name like kimi-k2-thinking-turbo typically have this capability. When using such models, the /model command won't prompt for thinking mode toggle.

image_in

When image input capability is enabled, you can paste images in conversations (Ctrl-V).

video_in

When video input capability is enabled, you can send video content in conversations.

Search and fetch services

The SearchWeb and FetchURL tools depend on external services, currently only provided by the Kimi Code platform.

When selecting the Kimi Code platform using /login, search and fetch services are automatically configured.

Service	Corresponding tool	Behavior when not configured
moonshot_search	SearchWeb	Tool unavailable
moonshot_fetch	FetchURL	Falls back to local fetching

When using other platforms, the FetchURL tool is still available but will fall back to local fetching.