> ## Documentation Index > Fetch the complete documentation index at: https://platform.minimax.io/docs/llms.txt > Use this file to discover all available pages before exploring further. # Estimate Input Tokens > Estimate the input token count of a request without invoking the model. Useful for evaluating request cost or checking context length limits before calling the main endpoint. ## OpenAPI ````yaml /api-reference/text/api/openapi-responses.json POST /v1/responses/input_tokens openapi: 3.1.0 info: title: MiniMax Responses API description: >- MiniMax OpenAI Responses API compatible endpoints, supporting chat generation and token estimation license: name: MIT version: 1.0.0 servers: - url: https://api.minimax.io security: - bearerAuth: [] paths: /v1/responses/input_tokens: post: tags: - Responses summary: Estimate Input Tokens operationId: estimateInputTokens parameters: - name: Content-Type in: header required: true description: Media type of the request body. Must be set to `application/json` schema: type: string enum: - application/json default: application/json requestBody: content: application/json: schema: $ref: '#/components/schemas/EstimateInputTokensReq' examples: Request: value: model: MiniMax-M3 input: - type: message role: user content: >- Please implement a generic quicksort algorithm in Python with these requirements: 1) in-place sorting to save memory; 2) three-way partitioning to handle duplicate elements; 3) switch to insertion sort for small subarrays; 4) include complete unit tests. Finally, explain the advantage of three-way partitioning over the classic Lomuto scheme when keys repeat. tools: - type: function name: search_docs description: >- Search the official documentation of the Python standard library or a third-party package parameters: type: object properties: library: type: string description: Library name, e.g. `typing`, `itertools` query: type: string description: Search keywords required: - library - query - type: function name: run_python description: >- Execute Python code in a sandbox and return stdout / error parameters: type: object properties: code: type: string description: Python code to execute timeout_seconds: type: integer description: Execution timeout in seconds default: 10 required: - code required: true responses: '200': description: Successful response content: application/json: schema: $ref: '#/components/schemas/EstimateInputTokensResp' examples: Response: value: object: response.input_tokens input_tokens: 588 components: schemas: EstimateInputTokensReq: type: object required: - model - input properties: model: type: string description: Model name to invoke, e.g. `MiniMax-M3` example: MiniMax-M3 input: description: >- Conversation content. Supports either a simple text or a full conversation history array oneOf: - type: string description: Simple text input - type: array description: Full conversation history items: $ref: '#/components/schemas/InputItem' instructions: type: string description: System instructions tools: type: array description: Tool list items: $ref: '#/components/schemas/Tool' tool_choice: type: string enum: - none - auto description: >- Tool selection strategy: `none` means no tool will be called; `auto` lets the model decide whether to call tools text: type: object description: Output format control properties: format: type: object properties: type: type: string enum: - text default: text description: Output format type reasoning: type: object description: >- Reasoning control. For MiniMax-M3, the default is `none`, which disables reasoning. Set `effort` to a non-`none` value (`minimal`, `low`, `medium`, or `high`) to enable Adaptive Thinking, but this does not tune MiniMax-M3's reasoning depth. For M2.x models, reasoning cannot be disabled. properties: effort: type: string enum: - minimal - low - medium - high - none default: none required: [] EstimateInputTokensResp: type: object required: - object - input_tokens properties: object: type: string enum: - response.input_tokens description: Object type, always `response.input_tokens` input_tokens: type: integer description: Estimated input token count InputItem: type: object description: >- Conversation history item. The `type` field determines the shape: `message` (default) / `function_call` / `function_call_output` / `reasoning` properties: type: type: string enum: - message - function_call - function_call_output - reasoning default: message description: Item type role: type: string enum: - user - assistant - system - developer - tool description: Message role (only when `type` is `message`) content: description: >- Message content; string or multimodal parts array (only when `type` is `message`) oneOf: - type: string - type: array items: $ref: '#/components/schemas/ContentPart' call_id: type: string description: >- Tool call ID (only when `type` is `function_call` or `function_call_output`) name: type: string description: Function name (only when `type` is `function_call`) arguments: type: string description: >- Function arguments as a JSON string (only when `type` is `function_call`) output: description: Tool return result (only when `type` is `function_call_output`) oneOf: - type: string - type: array items: $ref: '#/components/schemas/ContentPart' summary: type: array description: Reasoning segment array (only when `type` is `reasoning`) items: type: object properties: type: type: string enum: - summary_text text: type: string description: Reasoning text Tool: type: object required: - type - name properties: type: type: string enum: - function description: Tool type name: type: string description: Function name description: type: string description: Function description, helps the model decide when to call it parameters: type: object description: Function parameter definition in JSON Schema format ContentPart: type: object required: - type description: Message content part properties: type: type: string enum: - input_text - output_text - input_image - input_video description: |- Content part type: - `input_text` / `output_text`: Text part - `input_image`: Image input - `input_video`: Video input text: type: string description: Text content (when `type` is `input_text` / `output_text`) image_url: description: >- Image input (when `type` is `input_image`). Supported formats: JPEG, PNG, GIF, WEBP oneOf: - type: string - type: object required: - url properties: url: type: string description: Image URL or Base64 encoding detail: type: string enum: - low - default - high default: default description: Image understanding precision tier video_url: description: >- Video input (when `type` is `input_video`). Supported formats: MP4, AVI, MOV, MKV oneOf: - type: string - type: object required: - url properties: url: type: string description: >- Video URL or Base64 encoding. Use the File API to upload large files fps: type: number format: float default: 1 minimum: 0.2 maximum: 5 description: Frame extraction rate detail: type: string enum: - low - default - high default: default description: Video understanding precision tier max_long_side_pixel: type: integer description: Pixel constraint on the longest side of video frames securitySchemes: bearerAuth: type: http scheme: bearer bearerFormat: JWT description: |- `HTTP: Bearer Auth` - Security Scheme Type: http - HTTP Authorization Scheme: Bearer API_key, used to authenticate your account. View it in [Account Management > API Keys](https://platform.minimax.io/user-center/basic-information/interface-key) ````