ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter9/browser-use-rpa/browser-use/docs/customize/agent/supported-models.mdx

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+---
+title: "Supported Models"
+description: "Choose your favorite LLM"
+icon: "robot"
+
+---
+
+### Recommendations
+
+- Best accuracy: `O3`
+- Fastest: `llama4` on groq
+- Balanced: fast + cheap + clever: `gemini-2.5-flash` or `gpt-4.1-mini`
+
+
+### OpenAI [example](https://github.com/browser-use/browser-use/blob/main/examples/models/gpt-4.1.py)
+
+`O3` model is recommended for best performance.
+
+```python
+from browser_use import Agent, ChatOpenAI
+
+# Initialize the model
+llm = ChatOpenAI(
+    model="o3",
+)
+
+# Create agent with the model
+agent = Agent(
+    task="...", # Your task here
+    llm=llm
+)
+```
+
+Required environment variables:
+
+```bash .env
+OPENAI_API_KEY=
+```
+
+<Info>
+  You can use any OpenAI compatible model by passing the model name to the
+  `ChatOpenAI` class using a custom URL (or any other parameter that would go
+  into the normal OpenAI API call).
+</Info>
+
+### Anthropic [example](https://github.com/browser-use/browser-use/blob/main/examples/models/claude-4-sonnet.py)
+
+```python
+from browser_use import Agent, ChatAnthropic
+
+# Initialize the model
+llm = ChatAnthropic(
+    model="claude-sonnet-4-0",
+)
+
+# Create agent with the model
+agent = Agent(
+    task="...", # Your task here
+    llm=llm
+)
+```
+
+And add the variable:
+
+```bash .env
+ANTHROPIC_API_KEY=
+```
+
+### Azure OpenAI [example](https://github.com/browser-use/browser-use/blob/main/examples/models/azure_openai.py)
+
+```python
+from browser_use import Agent, ChatAzureOpenAI
+from pydantic import SecretStr
+import os
+
+# Initialize the model
+llm = ChatAzureOpenAI(
+    model="o4-mini",
+)
+
+# Create agent with the model
+agent = Agent(
+    task="...", # Your task here
+    llm=llm
+)
+```
+
+Required environment variables:
+
+```bash .env
+AZURE_OPENAI_ENDPOINT=https://your-endpoint.openai.azure.com/
+AZURE_OPENAI_API_KEY=
+```
+
+### Gemini [example](https://github.com/browser-use/browser-use/blob/main/examples/models/gemini.py)
+
+> [!IMPORTANT] `GEMINI_API_KEY` was the old environment var name, it should be called `GOOGLE_API_KEY` as of 2025-05.
+
+```python
+from browser_use import Agent, ChatGoogle
+from dotenv import load_dotenv
+
+# Read GOOGLE_API_KEY into env
+load_dotenv()
+
+# Initialize the model
+llm = ChatGoogle(model='gemini-2.5-flash')
+
+# Create agent with the model
+agent = Agent(
+    task="Your task here",
+    llm=llm
+)
+```
+
+Required environment variables:
+
+```bash .env
+GOOGLE_API_KEY=
+```
+
+### AWS Bedrock [example](https://github.com/browser-use/browser-use/blob/main/examples/models/aws.py)
+
+AWS Bedrock provides access to multiple model providers through a single API. We support both a general AWS Bedrock client and provider-specific convenience classes.
+
+#### General AWS Bedrock (supports all providers)
+
+```python
+from browser_use import Agent, ChatAWSBedrock
+
+# Works with any Bedrock model (Anthropic, Meta, AI21, etc.)
+llm = ChatAWSBedrock(
+    model="anthropic.claude-3-5-sonnet-20240620-v1:0",  # or any Bedrock model
+    aws_region="us-east-1",
+)
+
+# Create agent with the model
+agent = Agent(
+    task="Your task here",
+    llm=llm
+)
+```
+
+#### Anthropic Claude via AWS Bedrock (convenience class)
+
+```python
+from browser_use import Agent, ChatAnthropicBedrock
+
+# Anthropic-specific class with Claude defaults
+llm = ChatAnthropicBedrock(
+    model="anthropic.claude-3-5-sonnet-20240620-v1:0",
+    aws_region="us-east-1",
+)
+
+# Create agent with the model
+agent = Agent(
+    task="Your task here",
+    llm=llm
+)
+```
+
+#### AWS Authentication
+
+Required environment variables:
+
+```bash .env
+AWS_ACCESS_KEY_ID=
+AWS_SECRET_ACCESS_KEY=
+AWS_DEFAULT_REGION=us-east-1
+```
+
+You can also use AWS profiles or IAM roles instead of environment variables. The implementation supports:
+
+- Environment variables (`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, `AWS_DEFAULT_REGION`)
+- AWS profiles and credential files
+- IAM roles (when running on EC2)
+- Session tokens for temporary credentials
+- AWS SSO authentication (`aws_sso_auth=True`)
+
+## Groq [example](https://github.com/browser-use/browser-use/blob/main/examples/models/llama4-groq.py)
+
+```python
+from browser_use import Agent, ChatGroq
+
+llm = ChatGroq(model="meta-llama/llama-4-maverick-17b-128e-instruct")
+
+agent = Agent(
+    task="Your task here",
+    llm=llm
+)
+```
+
+Required environment variables:
+
+```bash .env
+GROQ_API_KEY=
+```
+
+## Ollama
+
+1. Install Ollama: https://github.com/ollama/ollama
+2. Run `ollama serve` to start the server 
+3. In a new terminal, install the model you want to use: `ollama pull llama3.1:8b` (this has 4.9GB)
+
+```python
+from browser_use import Agent, ChatOllama
+
+llm = ChatOllama(model="llama3.1:8b")
+```
+
+## Langchain
+
+[Example](https://github.com/browser-use/browser-use/blob/main/examples/models/langchain) on how to use Langchain with Browser Use.
+
+## Qwen [example](https://github.com/browser-use/browser-use/blob/main/examples/models/qwen.py)
+
+Currently, only `qwen-vl-max` is recommended for Browser Use. Other Qwen models, including `qwen-max`, have issues with the action schema format.
+Smaller Qwen models may return incorrect action schema formats (e.g., `actions: [{"go_to_url": "google.com"}]` instead of `[{"go_to_url": {"url": "google.com"}}]`). If you want to use other models, add concrete examples of the correct action format to your prompt.
+
+```python
+from browser_use import Agent, ChatOpenAI
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+# Get API key from https://modelstudio.console.alibabacloud.com/?tab=playground#/api-key
+api_key = os.getenv('ALIBABA_CLOUD')
+base_url = 'https://dashscope-intl.aliyuncs.com/compatible-mode/v1'
+
+llm = ChatOpenAI(model='qwen-vl-max', api_key=api_key, base_url=base_url)
+
+agent = Agent(
+    task="Your task here",
+    llm=llm,
+    use_vision=True
+)
+```
+
+Required environment variables:
+
+```bash .env
+ALIBABA_CLOUD=
+```
+
+
+## Other models (DeepSeek, Novita, X...)
+
+We support all other models that can be called via OpenAI compatible API. We are open to PRs for more providers.
+
+**Examples available:**
+- [DeepSeek](https://github.com/browser-use/browser-use/blob/main/examples/models/deepseek-chat.py)
+- [Novita](https://github.com/browser-use/browser-use/blob/main/examples/models/novita.py)
+- [OpenRouter](https://github.com/browser-use/browser-use/blob/main/examples/models/openrouter.py)