MODEL IDxai-grok-4-3
live

Grok 4.3

xAI
by xAI1M context

Grok 4.3 is xAI's flagship language model for agentic reasoning, strong instruction following, and minimal hallucinations. It supports text and image input, a 1 million token context window, configurable reasoning effort including non-reasoning mode, function calling, and structured outputs for production assistants, coding workflows, and long-context analysis.

Grok 4.3

API Options

Platform-level options for task execution and delivery.

taskType

stringrequiredvalue: textInference

Identifier for the type of task being performed

taskUUID

stringrequiredUUID v4

UUID v4 identifier for tracking tasks and matching async responses. Must be unique per task.

outputFormat

stringdefault: TEXT

Specifies the file format of the generated output. The available values depend on the task type and the specific model's capabilities.

    Allowed values1 value

    webhookURL

    stringURI

    Specifies a webhook URL where JSON responses will be sent via HTTP POST when generation tasks complete. For batch requests with multiple results, each completed item triggers a separate webhook call as it becomes available.

    Learn more1 resource

    deliveryMethod

    stringdefault: sync

    Determines how the API delivers task results.

    Allowed values3 values
    Returns complete results directly in the API response.
    Returns an immediate acknowledgment with the task UUID. Poll for results using getResponse.
    Streams results token-by-token as they are generated.
    Learn more1 resource

    includeCost

    booleandefault: false

    Include task cost in the response.

    includeUsage

    booleandefault: false

    Include token usage statistics in the response.

    numberResults

    integermin: 1max: 4default: 1

    Number of results to generate. Each result uses a different seed, producing variations of the same parameters.

    Core Parameters

    Primary parameters that define the task output.

    model

    stringrequiredvalue: xai-grok-4-3

    Identifier of the model to use for generation.

    Learn more3 resources

    seed

    integermin: 0max: 9223372036854776000

    Random seed for reproducible generation. When not provided, a random seed is generated in the unsigned 32-bit range.

    Learn more1 resource

    messages

    array of objectsrequiredmin items: 1

    Array of chat messages forming the conversation context. The final message must use the user role.

    Properties2 properties
    messages » role

    role

    stringrequired

    The role of the message author.

    Allowed values2 values
    messages » content

    content

    stringrequiredmin: 1

    The text content of the message.

    Settings

    Technical parameters to fine-tune the inference process. These must be nested inside the settings object.

    settings » temperature

    temperature

    floatmin: 0max: 2step: 0.01default: 1

    Controls randomness in generation. Lower values produce more deterministic outputs, higher values increase variation and creativity.

    settings » topP

    topP

    floatmin: 0max: 1step: 0.01default: 1

    Nucleus sampling parameter that controls diversity by limiting the probability mass. Lower values make outputs more focused, higher values increase diversity.

    settings » maxTokens

    maxTokens

    integermin: 1

    Maximum number of tokens to generate in the response.

    Controls how the model selects which tool to call. This only takes effect when tools are defined.

    Examples3 examples

    Let the model decide (default):

    "toolChoice": {
      "type": "auto"
    }

    Force a specific tool call:

    "toolChoice": {
      "type": "tool",
      "name": "get_weather"
    }

    Require any tool call:

    "toolChoice": {
      "type": "any"
    }
    Properties2 properties
    toolChoice » type

    type

    stringrequired

    Strategy the model uses to decide when and which tools to call.

    Allowed values4 values
    The model decides whether to call a tool based on the conversation context. This is the recommended default.
    The model must call at least one tool but chooses which one. Useful when you always need structured output.
    The model must call the specific tool identified by name. Use this to force a particular function call.
    The model will not call any tool, even if tools are defined. Useful for forcing a text-only response.
    toolChoice » name

    name

    string

    Name of the specific tool the model must call. Required when type is tool.

    tools

    array of objectsmin items: 1max items: 128

    An array of tool definitions that the model may call during generation. The model can invoke one or more tools based on the conversation context, outputting structured calls with arguments instead of (or alongside) free-text.

    For function tools, each definition requires:

    • type: "function"
    • name: Unique identifier (alphanumeric, hyphens, underscores; max 64 chars).
    • description: What the function does. The model uses this to decide when to call it.
    • schema: JSON Schema object describing the expected input arguments.

    The search tool is executed server-side by the provider. You don't need to handle the tool result yourself.

    The codeInterpreter tool is executed server-side by the provider. You don't need to handle the tool result yourself.

    Examples4 examples
    Function tool, weather lookup:
    "tools": [
      {
        "type": "function",
        "name": "get_weather",
        "description": "Get current weather for a city",
        "schema": {
          "type": "object",
          "properties": {
            "city": { "type": "string", "description": "City name" }
          },
          "required": ["city"]
        }
      }
    ],
    "toolChoice": { "type": "auto" }
    Built-in web search:
    "tools": [
      { "type": "search" }
    ]
    Built-in code interpreter:
    "tools": [
      { "type": "codeInterpreter" }
    ]
    Multiple function tools:
    "tools": [
      {
        "type": "function",
        "name": "search_products",
        "description": "Search the product catalog by query and filters.",
        "schema": {
          "type": "object",
          "properties": {
            "query": { "type": "string" },
            "category": { "type": "string" }
          },
          "required": ["query"]
        }
      },
      {
        "type": "function",
        "name": "add_to_cart",
        "description": "Add a product to the user's shopping cart.",
        "schema": {
          "type": "object",
          "properties": {
            "productId": { "type": "string" },
            "quantity": { "type": "integer", "minimum": 1 }
          },
          "required": ["productId"]
        }
      }
    ]
    Properties4 properties
    tools » type

    type

    stringrequired

    The kind of tool to make available to the model. User-defined functions require name and schema, while built-in tools (search, codeInterpreter) are executed server-side by the provider.

    Allowed values1 value
    tools » name

    name

    stringmax: 64

    Unique function name. Required for function tools.

    tools » description

    Explanation of what the function does, used by the model to decide when to call it.

    tools » schema

    schema

    object

    JSON Schema object describing the function's input parameters.