Skip to main content

Documentation Index

Fetch the complete documentation index at: https://mintlify.com/bolt-builder/bolt-cli/llms.txt

Use this file to discover all available pages before exploring further.

Bolt is model-agnostic by design. Under the hood it uses the Vercel AI SDK to speak to providers, which means any provider the SDK supports — Anthropic, OpenAI, Google, Amazon Bedrock, OpenRouter, and more — works out of the box. The provider and model catalog is sourced from models.dev, a community-maintained database of provider metadata and pricing.

​
Managing provider credentials

Use bolt providers (aliased as bolt auth) to add, list, and remove provider credentials.

​
Add or update credentials

bolt providers login
# or equivalently:
bolt auth login
This launches an interactive prompt to select a provider and enter credentials. To skip the interactive flow, pass flags directly: 
bolt providers login --provider anthropic
bolt providers login --provider openai --method "API key"

​
List configured providers

bolt providers list
# or:
bolt auth list
Displays all stored credentials and any provider API keys detected from environment variables.

​
Remove credentials

bolt providers logout
bolt providers logout anthropic

​
Environment variable authentication

For CI pipelines or headless environments, set the provider’s API key environment variable directly — no interactive login required. Common examples: 
export ANTHROPIC_API_KEY="sk-ant-..."
export OPENAI_API_KEY="sk-..."
export GOOGLE_GENERATIVE_AI_API_KEY="AIza..."
Bolt reads these variables automatically at startup. bolt providers list will surface which environment variables it detected.

​
Browsing available models

bolt models lists every model available across your configured providers. 
# List all models
bolt models

# Filter to one provider
bolt models anthropic

# Show cost and capability metadata
bolt models --verbose

# Refresh the model catalog from models.dev
bolt models --refresh
Run bolt models --verbose to see input/output token pricing for every model. This makes it easy to compare cost trade-offs before committing to a model for a long-running task.

​
Model identifier format

Models are always referenced in provider/model format: 
anthropic/claude-opus-4-5
openai/gpt-4o
google/gemini-2.5-pro
openrouter/anthropic/claude-opus-4-5
Use this format anywhere Bolt accepts a model — CLI flags, config files, and agent definitions.

​
Selecting a model at runtime

​
--model / -m flag

The --model flag is available on bolt run, bolt commit, and bolt review: 
bolt run --model anthropic/claude-opus-4-5 "refactor the payment module"
bolt commit --model openai/gpt-4o
bolt review --model google/gemini-2.5-pro --staged

​
--variant — controlling reasoning effort

Some models support configurable reasoning effort levels (e.g., Anthropic’s extended thinking, OpenAI’s reasoning models). Use --variant to select the effort tier: 
bolt run --variant high "design a distributed rate limiter"
bolt run --variant minimal "rename this variable"
The available variant values depend on the provider and model. Common values are minimal, low, medium, high, and max, but the exact set varies. Check your provider’s documentation or use bolt models --verbose to see supported variants for a given model.

​
--thinking — show reasoning blocks

When using a model that supports extended thinking, pass --thinking to surface the model’s chain-of-thought in the output: 
bolt run --model anthropic/claude-opus-4-5 --variant high --thinking \
  "why does the token refresh logic race in the auth service?"

​
Best-of-N parallel runs

--best-of fires the same prompt at multiple models in parallel, then uses a judge model to rank the responses and keep the best one: 
bolt run --best-of "anthropic/claude-opus-4-5,openai/gpt-4o,google/gemini-2.5-pro" \
  "implement a binary search tree with full test coverage"
The judge defaults to the model passed via --model, or to the first entry in the --best-of list if --model is not set. The flag accepts a comma-separated list of provider/model identifiers.
Best-of-N is especially useful for complex algorithmic problems or architecture decisions where different models may bring genuinely different approaches. Let Bolt run them in parallel and pick the winner automatically.

Build docs developers (and LLMs) love

Get started for freeTalk to us