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Supported LLM Models

skills/open-source/references/models.md

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Supported LLM Models

Table of Contents

Browser Use

Optimized for browser automation — highest accuracy, fastest speed, lowest token cost.

python
from browser_use import ChatBrowserUse
llm = ChatBrowserUse()                    # bu-latest (default)
llm = ChatBrowserUse(model='bu-2-0')      # Premium model

Env: BROWSER_USE_API_KEY — get at https://cloud.browser-use.com/new-api-key

Models & Pricing (per 1M tokens):

ModelInputCachedOutput
bu-1-0 (default)$0.20$0.02$2.00
bu-2-0 (premium)$0.60$0.06$3.50

Google Gemini

python
from browser_use import ChatGoogle
llm = ChatGoogle(model="gemini-flash-latest")

Env: GOOGLE_API_KEY (free at https://aistudio.google.com/app/u/1/apikey)

Note: GEMINI_API_KEY is deprecated, use GOOGLE_API_KEY.

OpenAI

python
from browser_use import ChatOpenAI
llm = ChatOpenAI(model="gpt-4.1-mini")
# o3 recommended for complex tasks
llm = ChatOpenAI(model="o3")

Env: OPENAI_API_KEY

Supports custom base_url for OpenAI-compatible APIs.

Anthropic

python
from browser_use import ChatAnthropic
llm = ChatAnthropic(model='claude-sonnet-4-0', temperature=0.0)

Env: ANTHROPIC_API_KEY

Azure OpenAI

python
from browser_use import ChatAzureOpenAI
llm = ChatAzureOpenAI(
    model="gpt-4o",
    api_version="2025-03-01-preview",
    azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),
)

Env: AZURE_OPENAI_ENDPOINT, AZURE_OPENAI_API_KEY

Supports Responses API for models like gpt-5.1-codex-mini.

AWS Bedrock

python
from browser_use import ChatAWSBedrock
llm = ChatAWSBedrock(model="us.anthropic.claude-sonnet-4-20250514-v1:0", region="us-east-1")

# Or via Anthropic wrapper
from browser_use import ChatAnthropicBedrock
llm = ChatAnthropicBedrock(model="us.anthropic.claude-sonnet-4-20250514-v1:0", aws_region="us-east-1")

Env: AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_DEFAULT_REGION

Supports profiles, IAM roles, SSO via standard AWS credential chain.

Groq

python
from browser_use import ChatGroq
llm = ChatGroq(model="meta-llama/llama-4-maverick-17b-128e-instruct")

Env: GROQ_API_KEY

OCI (Oracle)

python
from browser_use import ChatOCIRaw
llm = ChatOCIRaw(
    model="meta.llama-3.1-70b-instruct",
    service_endpoint="https://inference.generativeai.us-chicago-1.oci.oraclecloud.com",
    compartment_id="your-compartment-id",
)

Requires ~/.oci/config setup. Auth types: API_KEY, INSTANCE_PRINCIPAL, RESOURCE_PRINCIPAL.

Ollama (Local)

python
from browser_use import ChatOllama
llm = ChatOllama(model="llama3", num_ctx=32000)

Requires ollama serve running locally. Use num_ctx for context window (default may be too small).

Vercel AI Gateway

Proxy to multiple providers with automatic fallback:

python
from browser_use import ChatVercel
llm = ChatVercel(
    model='anthropic/claude-sonnet-4',
    provider_options={
        'gateway': {
            'order': ['vertex', 'anthropic'],  # Fallback order
        }
    },
)

Env: AI_GATEWAY_API_KEY (or VERCEL_OIDC_TOKEN on Vercel)

OpenAI-Compatible APIs

Any provider with an OpenAI-compatible endpoint works via ChatOpenAI:

Qwen (Alibaba)

python
llm = ChatOpenAI(model="qwen-vl-max", base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1")

Env: ALIBABA_CLOUD

ModelScope

python
llm = ChatOpenAI(model="Qwen/Qwen2.5-VL-72B-Instruct", base_url="https://api-inference.modelscope.cn/v1")

Env: MODELSCOPE_API_KEY

DeepSeek

python
llm = ChatOpenAI(model="deepseek-chat", base_url="https://api.deepseek.com")

Env: DEEPSEEK_API_KEY

Novita

python
llm = ChatOpenAI(model="deepseek/deepseek-r1", base_url="https://api.novita.ai/v3/openai")

Env: NOVITA_API_KEY

OpenRouter

python
llm = ChatOpenAI(model="deepseek/deepseek-r1", base_url="https://openrouter.ai/api/v1")

Env: OPENROUTER_API_KEY

Langchain

See example at examples/models/langchain.