> ## Documentation Index > Fetch the complete documentation index at: https://docs.evolink.ai/llms.txt > Use this file to discover all available pages before exploring further. # MiniMax-M2.5 - Complete API Reference > - Use OpenAI SDK format to call MiniMax-M2.5 model - Synchronous processing mode, real-time response - **Text conversation**: Single or multi-turn contextual dialogue - **System prompts**: Customize AI role and behavior **BaseURL**: The default BaseURL is `https://direct.evolink.ai`, which has better support for text models and long-lived connections. `https://api.evolink.ai` is the primary endpoint for multimodal services and serves as a fallback address for text models. ## OpenAPI ````yaml /en/api-manual/language-series/minimax-m2.5/minimax-m2.5-api.json POST /v1/chat/completions openapi: 3.1.0 info: title: MiniMax-M2.5 Complete API Reference description: Complete API reference for MiniMax-M2.5 chat interface license: name: MIT version: 1.0.0 servers: - url: https://direct.evolink.ai description: Production (recommended) - url: https://api.evolink.ai description: Alternative URL security: - bearerAuth: [] tags: - name: Chat Completion description: AI chat completion related endpoints paths: /v1/chat/completions: post: tags: - Chat Completion summary: MiniMax-M2.5 Chat Interface description: |- - Use OpenAI SDK format to call MiniMax-M2.5 model - Synchronous processing mode, real-time response - **Text conversation**: Single or multi-turn contextual dialogue - **System prompts**: Customize AI role and behavior operationId: createChatCompletion requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/ChatCompletionRequest' examples: simple_text: summary: Single-turn text conversation value: model: MiniMax-M2.5 messages: - role: user content: Please introduce yourself multi_turn: summary: Multi-turn conversation (context understanding) value: model: MiniMax-M2.5 messages: - role: user content: What is Python? - role: assistant content: Python is a high-level programming language... - role: user content: What are its advantages? system_prompt: summary: Using system prompts value: model: MiniMax-M2.5 messages: - role: system content: >- You are a professional Python programming assistant, answer questions concisely. - role: user content: How to read a file? responses: '200': description: Chat completion successful content: application/json: schema: $ref: '#/components/schemas/ChatCompletionResponse' '400': description: Invalid request parameters content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 400 message: Invalid request parameters type: invalid_request_error '401': description: Unauthenticated, invalid or expired token content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 401 message: Invalid or expired token type: authentication_error '402': description: Insufficient quota, recharge required content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 402 message: Insufficient quota type: insufficient_quota_error fallback_suggestion: https://evolink.ai/dashboard/billing '403': description: Access denied content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 403 message: Access denied for this model type: permission_error param: model '404': description: Resource not found content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 404 message: Specified model not found type: not_found_error param: model fallback_suggestion: MiniMax-M2.5 '429': description: Rate limit exceeded content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 429 message: Rate limit exceeded type: rate_limit_error fallback_suggestion: retry after 60 seconds '500': description: Internal server error content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 500 message: Internal server error type: internal_server_error fallback_suggestion: try again later '502': description: Upstream service error content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 502 message: Upstream AI service unavailable type: upstream_error fallback_suggestion: try different model '503': description: Service temporarily unavailable content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: error: code: 503 message: Service temporarily unavailable type: service_unavailable_error fallback_suggestion: retry after 30 seconds components: schemas: ChatCompletionRequest: type: object required: - model - messages properties: model: type: string description: Chat model name enum: - MiniMax-M2.5 example: MiniMax-M2.5 messages: type: array description: List of conversation messages, supports multi-turn dialogue items: $ref: '#/components/schemas/Message' minItems: 1 max_tokens: type: integer description: >- Maximum number of tokens for generated content, upper limit is 2048 **Note**: - Content exceeding the limit will be truncated - If generation is interrupted due to `length`, try increasing this value minimum: 1 maximum: 2048 example: 2048 stream: type: boolean description: |- Whether to return the response in streaming mode - `true`: Stream response, return content in real-time chunks - `false`: Wait for complete response before returning example: false temperature: type: number description: |- Sampling temperature, controls output randomness **Note**: - Lower values (e.g. 0.1): More deterministic, focused output - Higher values (e.g. 0.9): More random, creative output - Range: (0, 1], excluding 0 exclusiveMinimum: 0 maximum: 1 example: 0.7 top_p: type: number description: >- Nucleus Sampling parameter **Note**: - Controls sampling from tokens with cumulative probability - e.g. 0.9 means selecting from tokens reaching 90% cumulative probability - Range: (0, 1], excluding 0 **Recommendation**: Do not adjust temperature and top_p simultaneously exclusiveMinimum: 0 maximum: 1 example: 0.9 enable_search: type: boolean description: >- Whether to enable web search - `true`: Enable web search, the model will search the internet for latest information as needed - `false`: Disable web search example: true search_options: type: object description: 'Web search options, requires `enable_search: true`' properties: search_strategy: type: string description: |- Search strategy - `turbo`: Fast search, quicker speed - `max`: Deep search, more comprehensive results enum: - turbo - max example: max ChatCompletionResponse: type: object properties: id: type: string description: Unique identifier for the chat completion example: cmpl-04ea926191a14749b7f2c7a48a68abc6 model: type: string description: Model name actually used example: MiniMax-M2.5 object: type: string enum: - chat.completion description: Response type example: chat.completion created: type: integer description: Creation timestamp example: 1698999496 choices: type: array description: List of chat completion choices items: $ref: '#/components/schemas/Choice' usage: $ref: '#/components/schemas/Usage' ErrorResponse: type: object properties: error: type: object properties: code: type: integer description: HTTP status error code message: type: string description: Error description type: type: string description: Error type param: type: string description: Related parameter name fallback_suggestion: type: string description: Suggestion on error Message: type: object required: - role - content properties: role: type: string description: |- Message role - `user`: User message - `assistant`: AI assistant message (for multi-turn dialogue) - `system`: System prompt (define AI role and behavior) enum: - user - assistant - system example: user content: type: string description: Message content example: Please introduce yourself Choice: type: object properties: index: type: integer description: Choice index example: 0 message: $ref: '#/components/schemas/AssistantMessage' finish_reason: type: string description: |- Finish reason - `stop`: Normal completion - `length`: Reached maximum token limit - `content_filter`: Content filtered enum: - stop - length - content_filter example: stop Usage: type: object description: Token usage statistics properties: prompt_tokens: type: integer description: Number of tokens in the input example: 8 completion_tokens: type: integer description: Number of tokens in the output example: 292 total_tokens: type: integer description: Total number of tokens example: 300 AssistantMessage: type: object properties: role: type: string description: Role of the message sender enum: - assistant example: assistant content: type: string description: AI response message content example: Hi there! How can I help you? securitySchemes: bearerAuth: type: http scheme: bearer description: >- ##All APIs require Bearer Token authentication## **Get API Key:** Visit [API Key Management Page](https://evolink.ai/dashboard/keys) to get your API Key **Add to request header:** ``` Authorization: Bearer YOUR_API_KEY ``` ````