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Compatible Anthropic API
Call MiniMax models using the Anthropic SDK
To meet developers' needs for the Anthropic API ecosystem, our API now supports the Anthropic API format. With simple configuration, you can integrate MiniMax capabilities into the Anthropic API ecosystem.
Quick Start
1. Install Anthropic SDK
```bash Python theme={null} pip install anthropic ```npm install @anthropic-ai/sdk
2. Configure Environment Variables
For international users, use https://api.minimax.io/anthropic; for users in China, use https://api.minimaxi.com/anthropic
export ANTHROPIC_BASE_URL=https://api.minimax.io/anthropic
export ANTHROPIC_API_KEY=${YOUR_API_KEY}
3. Call API
import anthropic
client = anthropic.Anthropic()
message = client.messages.create(
model="MiniMax-M2.1",
max_tokens=1000,
system="You are a helpful assistant.",
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "Hi, how are you?"
}
]
}
]
)
for block in message.content:
if block.type == "thinking":
print(f"Thinking:\n{block.thinking}\n")
elif block.type == "text":
print(f"Text:\n{block.text}\n")
4. Important Note
In multi-turn function call conversations, the complete model response (i.e., the assistant message) must be append to the conversation history to maintain the continuity of the reasoning chain.
- Append the full
response.contentlist to the message history (includes all content blocks: thinking/text/tool_use)
Supported Models
When using the Anthropic SDK, the MiniMax-M2.1 MiniMax-M2.1-lightning MiniMax-M2 model is supported:
| Model Name | Description |
|---|---|
| MiniMax-M2.1 | Powerful Multi-Language Programming Capabilities with Comprehensively Enhanced Programming Experience (output speed approximately 60 tps) |
| MiniMax-M2.1-lightning | Faster and More Agile (output speed approximately 100 tps) |
| MiniMax-M2 | Agentic capabilities, Advanced reasoning |
Compatibility
Supported Parameters
When using the Anthropic SDK, we support the following input parameters:
| Parameter | Support Status | Description |
|---|---|---|
model |
Fully supported | supports MiniMax-M2.1 MiniMax-M2.1-lightning MiniMax-M2 model |
messages |
Partial support | Supports text and tool calls, no image/document input |
max_tokens |
Fully supported | Maximum number of tokens to generate |
stream |
Fully supported | Streaming response |
system |
Fully supported | System prompt |
temperature |
Fully supported | Range (0.0, 1.0], controls output randomness, recommended value: 1 |
tool_choice |
Fully supported | Tool selection strategy |
tools |
Fully supported | Tool definitions |
top_p |
Fully supported | Nucleus sampling parameter |
metadata |
Fully Supported | Metadata |
thinking |
Fully Supported | Reasoning Content |
top_k |
Ignored | This parameter will be ignored |
stop_sequences |
Ignored | This parameter will be ignored |
service_tier |
Ignored | This parameter will be ignored |
mcp_servers |
Ignored | This parameter will be ignored |
context_management |
Ignored | This parameter will be ignored |
container |
Ignored | This parameter will be ignored |
Messages Field Support
| Field Type | Support Status | Description |
|---|---|---|
type="text" |
Fully supported | Text messages |
type="tool_use" |
Fully supported | Tool calls |
type="tool_result" |
Fully supported | Tool call results |
type="thinking" |
Fully supported | Reasoning Content |
type="image" |
Not supported | Image input not supported yet |
type="document" |
Not supported | Document input not supported yet |
Examples
Streaming Response
import anthropic
client = anthropic.Anthropic()
print("Starting stream response...\n")
print("=" * 60)
print("Thinking Process:")
print("=" * 60)
stream = client.messages.create(
model="MiniMax-M2.1",
max_tokens=1000,
system="You are a helpful assistant.",
messages=[
{"role": "user", "content": [{"type": "text", "text": "Hi, how are you?"}]}
],
stream=True,
)
reasoning_buffer = ""
text_buffer = ""
for chunk in stream:
if chunk.type == "content_block_start":
if hasattr(chunk, "content_block") and chunk.content_block:
if chunk.content_block.type == "text":
print("\n" + "=" * 60)
print("Response Content:")
print("=" * 60)
elif chunk.type == "content_block_delta":
if hasattr(chunk, "delta") and chunk.delta:
if chunk.delta.type == "thinking_delta":
# Stream output thinking process
new_thinking = chunk.delta.thinking
if new_thinking:
print(new_thinking, end="", flush=True)
reasoning_buffer += new_thinking
elif chunk.delta.type == "text_delta":
# Stream output text content
new_text = chunk.delta.text
if new_text:
print(new_text, end="", flush=True)
text_buffer += new_text
print("\n")
Tool Use & Interleaved Thinking
Learn how to use M2.1 Tool Use and Interleaved Thinking capabilities with Anthropic SDK, please refer to the following documentation.
Learn how to leverage MiniMax-M2.1 tool calling and interleaved thinking capabilities to enhance performance in complex tasks.Important Notes
1. The Anthropic API compatibility interface currently only supports the `MiniMax-M2.1` `MiniMax-M2` model-
The
temperatureparameter range is (0.0, 1.0], values outside this range will return an error -
Some Anthropic parameters (such as
thinking,top_k,stop_sequences,service_tier,mcp_servers,context_management,container) will be ignored -
Image and document type inputs are not currently supported
Related Links
Recommended Reading
Supports text generation via compatible Anthropic API and OpenAI API. Use OpenAI SDK with MiniMax models MiniMax-M2.1 excels at code understanding, dialogue, and reasoning. AI models can call external functions to extend their capabilities.To find navigation and other pages in this documentation, fetch the llms.txt file at: https://platform.minimax.io/docs/llms.txt