---
title: "Creates a model response for the given chat conversation."
method: POST
path: "/openai/v1/chat/completions"
tags: ["Chat"]
---

# Creates a model response for the given chat conversation.

`POST /openai/v1/chat/completions`

## Request body

- CreateChatCompletionRequest
  - `messages` ChatCompletionRequestMessage[], required — A list of messages comprising the conversation so far.
    - union
      - ChatCompletionRequestSystemMessage
        - `content` union, required — The contents of the system message.
          - string — The text contents of the message.
          - ChatCompletionRequestMessageContentPartText[] — An array of content parts with a defined type, only `text` is supported for this message type.
            - `type` 'text', required — The type of the content part.
            - `text` string, required — The text content.
        - `role` 'system' | 'developer', required — The role of the messages author, in this case `system`.
        - `name` string — An optional name for the participant. Provides the model information to differentiate between participants of the same role.
      - ChatCompletionRequestUserMessage
        - `content` union, required — The contents of the user message.
          - string — The text contents of the message.
          - ChatCompletionRequestMessageContentPart[] — An array of content parts with a defined type, each can be of type `text` or `image_url` when passing in images. You can pass multiple images by adding multiple `image_url` content parts. Image input is only supported when using the `gpt-4-visual-preview` model.
            - union
              - …
        - `role` 'user', required — The role of the messages author, in this case `user`.
        - `name` string — An optional name for the participant. Provides the model information to differentiate between participants of the same role.
      - ChatCompletionRequestAssistantMessage
        - `content` union — The contents of the assistant message. Required unless `tool_calls` or `function_call` is specified.
          - string — The text contents of the message.
          - ChatCompletionRequestMessageContentPartText[] — An array of content parts with a defined type, only `text` is supported for this message type.
            - `type` 'text', required — The type of the content part.
            - `text` string, required — The text content.
        - `reasoning` string, nullable — The reasoning output by the assistant if reasoning_format was set to 'parsed'. This field is supported on [models that support reasoning](https://console.groq.com/docs/reasoning).
        - `role` 'assistant', required — The role of the messages author, in this case `assistant`.
        - `name` string — An optional name for the participant. Provides the model information to differentiate between participants of the same role.
        - `tool_calls` ChatCompletionMessageToolCall[] — The tool calls generated by the model, such as function calls.
          - `id` string, required — The ID of the tool call.
          - `type` 'function', required — The type of the tool. Currently, only `function` is supported.
          - `function` object, required — The function that the model called.
            - `name` string, required — The name of the function to call.
            - `arguments` string, required — The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.
        - `function_call` object — Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be called, as generated by the model.
          - `arguments` string — The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.
          - `name` string — The name of the function to call.
      - ChatCompletionRequestToolMessage
        - `role` 'tool', required — The role of the messages author, in this case `tool`.
        - `content` union, required — The contents of the tool message.
          - string — The text contents of the message.
          - ChatCompletionRequestMessageContentPart[] — An array of content parts with a defined type, each can be of type `text` or `image_url` when passing in images. You can pass multiple images by adding multiple `image_url` content parts. Image input is only supported when using the `gpt-4-visual-preview` model.
            - union
              - …
        - `tool_call_id` string, required — Tool call that this message is responding to.
      - ChatCompletionRequestFunctionMessage
        - `role` 'function', required — The role of the messages author, in this case `function`.
        - `content` string, nullable, required — The contents of the function message.
        - `name` string, required — The name of the function to call.
  - `model` union, required — ID of the model to use. For details on which models are compatible with the Chat API, see available [models](https://console.groq.com/docs/models)
    - string
    - 'compound-beta' | 'compound-beta-mini' | 'gemma2-9b-it' | 'llama-3.1-8b-instant' | 'llama-3.3-70b-versatile' | 'meta-llama/llama-4-maverick-17b-128e-instruct' | 'meta-llama/llama-4-scout-17b-16e-instruct' | 'meta-llama/llama-guard-4-12b' | 'moonshotai/kimi-k2-instruct' | 'openai/gpt-oss-120b' | 'openai/gpt-oss-20b' | 'qwen/qwen3-32b' | 'qwen/qwen3.6-27b'
  - `disable_tool_validation` boolean — If set to true, groq will return called tools without validating that the tool is present in request.tools. tool_choice=required/none will still be enforced, but the request cannot require a specific tool be used.
  - `frequency_penalty` number, nullable — This is not yet supported by any of our models. Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
  - `include_reasoning` boolean, nullable — Whether to include reasoning in the response. If true, the response will include a `reasoning` field. If false, the model's reasoning will not be included in the response. This field is mutually exclusive with `reasoning_format`.
  - `logit_bias` object, nullable — This is not yet supported by any of our models. Modify the likelihood of specified tokens appearing in the completion.
  - `logprobs` boolean, nullable — This is not yet supported by any of our models. Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the `content` of `message`.
  - `top_logprobs` integer, nullable — This is not yet supported by any of our models. An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. `logprobs` must be set to `true` if this parameter is used.
  - `max_tokens` integer, nullable — Deprecated in favor of `max_completion_tokens`. The maximum number of tokens that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length.
  - `max_completion_tokens` integer, nullable — The maximum number of tokens that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length.
  - `n` integer, nullable — How many chat completion choices to generate for each input message. Note that the current moment, only n=1 is supported. Other values will result in a 400 response.
  - `presence_penalty` number, nullable — This is not yet supported by any of our models. Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
  - `response_format` union — An object specifying the format that the model must output. Setting to `{ "type": "json_schema", "json_schema": {...} }` enables Structured Outputs which ensures the model will match your supplied JSON schema. `json_schema` response format is only available on [supported models](https://console.groq.com/docs/structured-outputs#supported-models). Setting to `{ "type": "json_object" }` enables the older JSON mode, which ensures the message the model generates is valid JSON. Using `json_schema` is preferred for models that support it.
    - ResponseFormatText — Default response format. Used to generate text responses.
      - `type` 'text', required — The type of response format being defined. Always `text`.
    - ResponseFormatJsonSchema — JSON Schema response format. Used to generate structured JSON responses.
      - `type` 'json_schema', required — The type of response format being defined. Always `json_schema`.
      - `json_schema` object, required — Structured Outputs configuration options, including a JSON Schema.
        - `description` string — A description of what the response format is for, used by the model to determine how to respond in the format.
        - `name` string, required — The name of the response format. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.
        - `schema` ResponseFormatJsonSchemaSchema — The schema for the response format, described as a JSON Schema object. Learn how to build JSON schemas [here](https://json-schema.org/).
        - `strict` boolean, nullable — Whether to enable strict schema adherence when generating the output. If set to true, the model will always follow the exact schema defined in the `schema` field. Only a subset of JSON Schema is supported when `strict` is `true`.
    - ResponseFormatJsonObject — JSON object response format. An older method of generating JSON responses. Using `json_schema` is recommended for models that support it. Note that the model will not generate JSON without a system or user message instructing it to do so.
      - `type` 'json_object', required — The type of response format being defined. Always `json_object`.
  - `seed` integer, nullable — If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result. Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend.
  - `service_tier` 'auto' | 'on_demand' | 'flex' | 'performance' | 'null', nullable — The service tier to use for the request. Defaults to `on_demand`. - `auto` will automatically select the highest tier available within the rate limits of your organization. - `flex` uses the flex tier, which will succeed or fail quickly.
  - `stop` union — Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.
    - string, nullable
    - string[]
  - `reasoning_effort` 'none' | 'default' | 'low' | 'medium' | 'high', nullable — qwen3 models support the following values Set to 'none' to disable reasoning. Set to 'default' or null to let Qwen reason. openai/gpt-oss-20b and openai/gpt-oss-120b support 'low', 'medium', or 'high'. 'medium' is the default value.
  - `reasoning_format` 'hidden' | 'raw' | 'parsed', nullable — Specifies how to output reasoning tokens This field is mutually exclusive with `include_reasoning`.
  - `stream` boolean, nullable — If set, partial message deltas will be sent. Tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]` message. [Example code](/docs/text-chat#streaming-a-chat-completion).
  - `temperature` number, nullable — What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or top_p but not both.
  - `top_p` number, nullable — An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.
  - `tools` ChatCompletionTool[], nullable — A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.
    - `type` union, required
      - 'function' | 'browser_search' | 'code_interpreter' — The type of the tool. `function`, `browser_search`, and `code_interpreter` are supported.
      - string
    - `function` FunctionObject
      - `description` string — A description of what the function does, used by the model to choose when and how to call the function.
      - `name` string, required — The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.
      - `parameters` FunctionParameters — Function parameters defined as a JSON Schema object. Refer to https://json-schema.org/understanding-json-schema/ for schema documentation.
      - `strict` boolean — Whether to enable strict schema adherence when generating the output. If set to true, the model will always follow the exact schema defined in the `schema` field. Only a subset of JSON Schema is supported when `strict` is `true`.
  - `tool_choice` union — Controls which (if any) tool is called by the model. `none` means the model will not call any tool and instead generates a message. `auto` means the model can pick between generating a message or calling one or more tools. `required` means the model must call one or more tools. Specifying a particular tool via `{"type": "function", "function": {"name": "my_function"}}` forces the model to call that tool. `none` is the default when no tools are present. `auto` is the default if tools are present.
    - 'none' | 'auto' | 'required' — `none` means the model will not call any tool and instead generates a message. `auto` means the model can pick between generating a message or calling one or more tools.
    - object — Specifies a tool the model should use. Use to force the model to call a specific function.
      - `type` 'function', required — The type of the tool. Currently, only `function` is supported.
      - `function` object, required
        - `name` string, required — The name of the function to call.
  - `parallel_tool_calls` boolean, nullable — Whether to enable parallel function calling during tool use.
  - `user` string, nullable — A unique identifier representing your end-user, which can help us monitor and detect abuse.
  - `function_call` union — Deprecated in favor of `tool_choice`. Controls which (if any) function is called by the model. `none` means the model will not call a function and instead generates a message. `auto` means the model can pick between generating a message or calling a function. Specifying a particular function via `{"name": "my_function"}` forces the model to call that function. `none` is the default when no functions are present. `auto` is the default if functions are present.
    - 'none' | 'auto' | 'required' — `none` means the model will not call a function and instead generates a message. `auto` means the model can pick between generating a message or calling a function.
    - ChatCompletionFunctionCallOption — Specifying a particular function via `{"name": "my_function"}` forces the model to call that function.
      - `name` string, required — The name of the function to call.
  - `functions` ChatCompletionFunctions[], nullable — Deprecated in favor of `tools`. A list of functions the model may generate JSON inputs for.
    - `description` string — A description of what the function does, used by the model to choose when and how to call the function.
    - `name` string, required — The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.
    - `parameters` FunctionParameters — Function parameters defined as a JSON Schema object. Refer to https://json-schema.org/understanding-json-schema/ for schema documentation.
  - `metadata` object, nullable — This parameter is not currently supported.
  - `store` boolean, nullable — This parameter is not currently supported.
  - `include_domains` string[], nullable — Deprecated: Use search_settings.include_domains instead. A list of domains to include in the search results when the model uses a web search tool.
  - `exclude_domains` string[], nullable — Deprecated: Use search_settings.exclude_domains instead. A list of domains to exclude from the search results when the model uses a web search tool.
  - `search_settings` object, nullable — Settings for web search functionality when the model uses a web search tool.
    - `include_domains` string[], nullable — A list of domains to include in the search results.
    - `exclude_domains` string[], nullable — A list of domains to exclude from the search results.
    - `include_images` boolean, nullable — Whether to include images in the search results.
    - `country` string, nullable — Name of country to prioritize search results from (e.g., "united states", "germany", "france").
  - `compound_custom` object, nullable — Custom configuration of models and tools for Compound.
    - `models` object, nullable
      - `reasoning_model` string, nullable — Custom model to use for reasoning.
      - `answering_model` string, nullable — Custom model to use for answering.
    - `tools` object, nullable — Configuration options for tools available to Compound.
      - `enabled_tools` string[], nullable — A list of tool names that are enabled for the request.
      - `wolfram_settings` object, nullable — Configuration for the Wolfram tool integration.
        - `authorization` string, nullable — API key used to authorize requests to Wolfram services.
  - `documents` ChatCompletionDocument[], nullable — A list of documents to provide context for the conversation. Each document contains text that can be referenced by the model.
    - `id` string, nullable — Optional unique identifier that can be used for citations in responses.
    - `source` union, required — The source of the document. Only text and JSON sources are currently supported.
      - ChatCompletionDocumentSourceText — A document whose contents are provided inline as text.
        - `type` 'text', required — Identifies this document source as inline text.
        - `text` string, required — The document contents.
      - ChatCompletionDocumentSourceJSON — A document whose contents are provided inline as JSON data.
        - `type` 'json', required — Identifies this document source as JSON data.
        - `data` object, required — The JSON payload associated with the document.
  - `citation_options` 'enabled' | 'disabled', nullable — Whether to enable citations in the response. When enabled, the model will include citations for information retrieved from provided documents or web searches.

## Response `200`

OK

- CreateChatCompletionResponse — Represents a chat completion response returned by model, based on the provided input.
  - `id` string, required — A unique identifier for the chat completion.
  - `choices` object[], required — A list of chat completion choices. Can be more than one if `n` is greater than 1.
    - `finish_reason` 'stop' | 'length' | 'tool_calls' | 'function_call', required — The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, `length` if the maximum number of tokens specified in the request was reached, `tool_calls` if the model called a tool, or `function_call` (deprecated) if the model called a function.
    - `index` integer, required — The index of the choice in the list of choices.
    - `message` ChatCompletionResponseMessage, required — A chat completion message generated by the model.
      - `content` string, nullable, required — The contents of the message.
      - `reasoning` string, nullable — The model's reasoning for a response. Only available for [models that support reasoning](https://console.groq.com/docs/reasoning) when request parameter reasoning_format has value `parsed`.
      - `tool_calls` ChatCompletionMessageToolCall[] — The tool calls generated by the model, such as function calls.
        - `id` string, required — The ID of the tool call.
        - `type` 'function', required — The type of the tool. Currently, only `function` is supported.
        - `function` object, required — The function that the model called.
          - `name` string, required — The name of the function to call.
          - `arguments` string, required — The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.
      - `executed_tools` object[] — A list of tools that were executed during the chat completion for compound AI systems.
        - `index` integer, required — The index of the executed tool.
        - `type` string, required — The type of tool that was executed.
        - `arguments` string, required — The arguments passed to the tool in JSON format.
        - `output` string, nullable — The output returned by the tool.
        - `search_results` object, nullable — The search results returned by the tool, if applicable.
          - `results` object[] — List of search results
            - `title` string — The title of the search result
            - `url` string — The URL of the search result
            - `content` string — The content of the search result
            - `score` number, float — The relevance score of the search result
          - `images` string[] — List of image URLs returned by the search
        - `code_results` CodeExecutionResult[] — Array of code execution results
          - `text` string — The text version of the code execution result
          - `png` string — Base64 encoded PNG image output from code execution
          - `chart` Chart
            - `type` 'bar' | 'box_and_whisker' | 'line' | 'pie' | 'scatter' | 'superchart' | 'unknown', required — The type of chart
            - `title` string — The title of the chart
            - `x_label` string — The label for the x-axis
            - `y_label` string — The label for the y-axis
            - `x_unit` string — The unit for the x-axis
            - `y_unit` string — The unit for the y-axis
            - `x_ticks` number[] — The tick values for the x-axis
            - `y_ticks` number[] — The tick values for the y-axis
            - `x_tick_labels` string[] — The labels for the x-axis ticks
            - `y_tick_labels` string[] — The labels for the y-axis ticks
            - `x_scale` string — The scale type for the x-axis
            - `y_scale` string — The scale type for the y-axis
            - `elements` ChartElement[], required — The chart elements (data series, points, etc.)
              - …
          - `charts` Chart[] — Array of charts from a superchart
            - `type` 'bar' | 'box_and_whisker' | 'line' | 'pie' | 'scatter' | 'superchart' | 'unknown', required — The type of chart
            - `title` string — The title of the chart
            - `x_label` string — The label for the x-axis
            - `y_label` string — The label for the y-axis
            - `x_unit` string — The unit for the x-axis
            - `y_unit` string — The unit for the y-axis
            - `x_ticks` number[] — The tick values for the x-axis
            - `y_ticks` number[] — The tick values for the y-axis
            - `x_tick_labels` string[] — The labels for the x-axis ticks
            - `y_tick_labels` string[] — The labels for the y-axis ticks
            - `x_scale` string — The scale type for the x-axis
            - `y_scale` string — The scale type for the y-axis
            - `elements` ChartElement[], required — The chart elements (data series, points, etc.)
              - …
        - `browser_results` BrowserResult[] — Array of browser results
          - `url` string, required — The URL of the browser window
          - `title` string, required — The title of the browser window
          - `live_view_url` string — The live view URL for the browser window
          - `content` string — The content of the browser result
      - `role` 'assistant', required — The role of the author of this message.
      - `function_call` object — Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be called, as generated by the model.
        - `arguments` string, required — The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.
        - `name` string, required — The name of the function to call.
      - `annotations` Annotation[] — A list of annotations providing citations and references for the content in the message.
        - `type` 'document_citation' | 'function_citation', required — The type of annotation.
        - `document_citation` DocumentCitation — A citation referencing a specific document that was provided in the request.
          - `start_index` integer, required — The character index in the message content where this citation begins.
          - `end_index` integer, required — The character index in the message content where this citation ends.
          - `document_id` string, required — The ID of the document being cited, corresponding to a document provided in the request.
        - `function_citation` FunctionCitation — A citation referencing the result of a function or tool call.
          - `start_index` integer, required — The character index in the message content where this citation begins.
          - `end_index` integer, required — The character index in the message content where this citation ends.
          - `tool_call_id` string, required — The ID of the tool call being cited, corresponding to a tool call made during the conversation.
    - `logprobs` object, nullable, required — Log probability information for the choice.
      - `content` ChatCompletionTokenLogprob[], nullable, required — A list of message content tokens with log probability information.
        - `token` string, required — The token.
        - `logprob` number, required — The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value `-9999.0` is used to signify that the token is very unlikely.
        - `bytes` integer[], nullable, required — A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be `null` if there is no bytes representation for the token.
        - `top_logprobs` object[], required — List of the most likely tokens and their log probability, at this token position. In rare cases, there may be fewer than the number of requested `top_logprobs` returned.
          - `token` string, required — The token.
          - `logprob` number, required — The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value `-9999.0` is used to signify that the token is very unlikely.
          - `bytes` integer[], nullable, required — A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be `null` if there is no bytes representation for the token.
  - `created` integer, required — The Unix timestamp (in seconds) of when the chat completion was created.
  - `model` string, required — The model used for the chat completion.
  - `system_fingerprint` string — This fingerprint represents the backend configuration that the model runs with. Can be used in conjunction with the `seed` request parameter to understand when backend changes have been made that might impact determinism.
  - `object` 'chat.completion', required — The object type, which is always `chat.completion`.
  - `usage` CompletionUsage — Usage statistics for the completion request.
    - `queue_time` number — Time the requests was spent queued
    - `completion_time` number — Time spent generating tokens
    - `completion_tokens` integer, required — Number of tokens in the generated completion.
    - `prompt_time` number — Time spent processing input tokens
    - `prompt_tokens` integer, required — Number of tokens in the prompt.
    - `total_time` number — completion time and prompt time combined
    - `total_tokens` integer, required — Total number of tokens used in the request (prompt + completion).
    - `prompt_tokens_details` object, nullable — Breakdown of tokens in the prompt.
      - `cached_tokens` integer, required — Number of tokens that were cached and reused.
    - `completion_tokens_details` object, nullable — Breakdown of tokens in the completion.
      - `reasoning_tokens` integer, required — Number of tokens used for reasoning (for reasoning models).
  - `usage_breakdown` ChatCompletionUsageBreakdown — Usage statistics for compound AI completion requests.
    - `models` object[], required — List of models used in the request and their individual usage statistics
      - `model` string, required — The name/identifier of the model used
      - `usage` CompletionUsage, required — Usage statistics for the completion request.
        - `queue_time` number — Time the requests was spent queued
        - `completion_time` number — Time spent generating tokens
        - `completion_tokens` integer, required — Number of tokens in the generated completion.
        - `prompt_time` number — Time spent processing input tokens
        - `prompt_tokens` integer, required — Number of tokens in the prompt.
        - `total_time` number — completion time and prompt time combined
        - `total_tokens` integer, required — Total number of tokens used in the request (prompt + completion).
        - `prompt_tokens_details` object, nullable — Breakdown of tokens in the prompt.
          - `cached_tokens` integer, required — Number of tokens that were cached and reused.
        - `completion_tokens_details` object, nullable — Breakdown of tokens in the completion.
          - `reasoning_tokens` integer, required — Number of tokens used for reasoning (for reasoning models).
  - `service_tier` 'auto' | 'on_demand' | 'flex' | 'performance' | 'null', nullable — The service tier used for the request.
  - `mcp_list_tools` object[], nullable — List of discovered MCP tools from connected servers.
    - `id` string — Unique identifier for this tool list response.
    - `type` string — The type identifier.
    - `server_label` string — Human-readable label for the MCP server.
    - `tools` object[] — Array of discovered tools from the server.
      - `annotations` unknown
      - `description` string — Description of what the tool does.
      - `input_schema` object — JSON Schema describing the tool's input parameters.
      - `name` string — The name of the tool.
  - `x_groq` XGroqNonStreaming — Groq-specific metadata for non-streaming chat completion responses.
    - `id` string, required — A groq request ID which can be used to refer to a specific request to groq support.
    - `seed` integer, nullable — The seed used for the request. See the seed property on CreateChatCompletionRequest for more details.
    - `usage` object, nullable — Additional Groq-specific usage metrics (hardware cache statistics).
      - `sram_cached_tokens` integer — Number of tokens served from SRAM cache.
      - `dram_cached_tokens` integer — Number of tokens served from DRAM cache.
    - `debug` DebugData — Debug information including input and output token IDs and strings. Only present when debug=true in the request.
      - `input_token_ids` integer[] — Token IDs for the input.
      - `input_tokens` string[] — Token strings for the input.
      - `output_token_ids` integer[] — Token IDs for the output.
      - `output_tokens` string[] — Token strings for the output.

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[API](https://skmtc.net/groq/apis/groqcloud-api.md) · [All operations](https://skmtc.net/groq/apis/groqcloud-api/llms.txt) · [OpenAPI document](https://skmtc-service-staging.skmtc.workers.dev/v1/apis/groq/groqcloud-api/versions/ea91f46f212a/schema)