Providers and models

Kimi Code CLI supports connecting to multiple LLM platforms simultaneously — one-click login via the Kimi Code managed service, connecting Claude with an Anthropic API key, or connecting third-party inference services via the OpenAI-compatible protocol. Each provider corresponds to a specific API protocol; models are declared on top of providers with their own name, context length, and capabilities. This page explains how to configure each type of provider in config.toml.

Supported provider types

The type field in the providers table determines which protocol implementation to use:

Type	Protocol	Typical use
kimi	OpenAI-compatible	Kimi Code managed service, Kimi Platform API key
anthropic	Anthropic Messages	Claude model family
openai	OpenAI Chat Completions	OpenAI and compatible services, DeepSeek, Qwen, etc.
openai_responses	OpenAI Responses API	OpenAI's newer Responses interface
google-genai	Google GenAI	Gemini API
vertexai	Google GenAI on Vertex	Google Cloud Vertex AI

All providers communicate with models in streaming mode by default. Capabilities such as thinking, vision, and tool use are matched automatically by model name prefix — you typically do not need to declare them manually.

Credential priority: api_key direct field > [providers.<name>.env] sub-table key > if both are absent, startup fails with an error. The CLI does not fall back to shell environment variables for credentials — see Config overrides: provider credentials.

/provider — interactive provider management

Prefer not to edit TOML by hand? Type /provider in the TUI to open the provider manager, where you can interactively add or remove providers.

The manager displays providers as a list of entries grouped by source. Navigation:

• ↑/↓ to move the cursor, ←/→ to page
• d to delete the current provider (with [y/N] confirmation)
• Press Enter on the [ Add New Platform ] row to add a new provider

Two paths when adding:

• Known third-party provider: fetches the model catalog from models.dev, select a provider → enter an API key → select a default model
• Custom registry (api.json): paste a custom registry URL and Bearer token; the CLI automatically creates the providers / models entries

WARNING

Kimi Code OAuth managed accounts logged in via /login do not appear in /provider. Use /login and /logout to manage them.

The same operations are also available in non-interactive environments via the shell command: kimi provider.

kimi

For connecting to Moonshot AI's OpenAI-compatible interface, including the Kimi Code managed service and Kimi Platform API keys.

• Default base_url: https://api.moonshot.ai/v1
• Credential key names: KIMI_API_KEY, KIMI_BASE_URL
• Additional capability: supports video upload

[providers.kimi]
type = "kimi"
base_url = "https://api.moonshot.ai/v1"
api_key = "sk-xxxxx"

When using the Kimi Code managed service, running /login automatically configures base_url and credentials — no manual setup needed.

anthropic

For connecting to the Claude API. Standard Claude models automatically enable vision, tool use, and Thinking (where supported); custom or uncovered models need capabilities declared explicitly on [models.<alias>].

• Default base_url: follows Anthropic SDK default
• Credential key names: ANTHROPIC_API_KEY, ANTHROPIC_BASE_URL
• Default max_tokens: inferred per model. To override, set max_output_size on the model alias

[providers.anthropic]
type = "anthropic"
api_key = "sk-ant-xxxxx"

[models."claude-opus-4-7"]
provider = "anthropic"
model = "claude-opus-4-7"
max_context_size = 200000
# max_output_size = 32000  # optional; omit to use the model-inferred default

openai

For connecting to the OpenAI Chat Completions protocol, as well as any third-party service compatible with that protocol (override base_url as needed).

Third-party reasoning models (DeepSeek, Qwen, One API, etc.) work out of the box: the CLI automatically handles the reasoning_content field and reasoning_effort injection. If your gateway returns reasoning content under a non-standard field name, set reasoning_key on the model alias to override.

• Default base_url: https://api.openai.com/v1
• Credential key names: OPENAI_API_KEY, OPENAI_BASE_URL

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

openai_responses

Corresponds to OpenAI's newer Responses API, always operating in streaming mode. Configuration is the same as openai.

• Default base_url: https://api.openai.com/v1
• Credential key names: OPENAI_API_KEY, OPENAI_BASE_URL

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

google-genai

For connecting directly to the Google Gemini API. Thinking, vision, and multimodal capabilities are auto-detected by model name.

• Credential key name: GOOGLE_API_KEY

[providers.gemini]
type = "google-genai"
api_key = "xxxxx"

vertexai

Shares the same implementation as google-genai; setting type = "vertexai" switches to the Vertex AI access path.

Authentication follows the standard Google Cloud ADC flow (gcloud auth application-default login or a GOOGLE_APPLICATION_CREDENTIALS service account JSON) — this part is unrelated to Kimi Code. The project ID and region must be written in the [providers.vertexai.env] sub-table — simply export GOOGLE_CLOUD_PROJECT in the shell will not be read by the CLI.

[providers.vertexai]
type = "vertexai"

[providers.vertexai.env]
GOOGLE_CLOUD_PROJECT = "my-gcp-project"
GOOGLE_CLOUD_LOCATION = "us-central1"

gcloud auth application-default login   # one-time authentication
kimi

OAuth and credential injection

The Kimi Code managed service uses OAuth rather than static API keys. After running /login, the built-in authentication toolchain automatically writes and refreshes credentials — no manual configuration is needed in config.toml for this.

Next steps

• Configuration files — full field reference for the providers and models tables
• Config overrides — credential resolution priority rules for providers
• Environment variables — credential key names per provider type