resources/chat/subresources/completions/methods/create/index.md 2026-07-30 23:58 UTC to 2026-07-31 21:03 UTC

Create chat completion

post /chat/completions

Starting a new project? We recommend trying Responses to take advantage of the latest OpenAI platform features. Compare Chat Completions with Responses.

Creates a model response for the given chat conversation. Learn more in the text generation, vision, and audio guides.

Parameter support can differ depending on the model used to generate the response, particularly for newer reasoning models. Parameters that are only supported for reasoning models are noted below. For the current state of unsupported parameters in reasoning models, refer to the reasoning guide.

Returns a chat completion object, or a streamed sequence of chat completion chunk objects if the request is streamed.

Body Parameters

• messages: array of ChatCompletionMessageParam

  A list of messages comprising the conversation so far. Depending on the model you use, different message types (modalities) are supported, like text, images, and audio.

  • ChatCompletionDeveloperMessageParam object { content, role, name }

    Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, developer messages replace the previous system messages.

    • content: string or array of ChatCompletionContentPartText

      The contents of the developer message.

      • TextContent = string

        The contents of the developer message.

      • ArrayOfContentParts = array of ChatCompletionContentPartText

        An array of content parts with a defined type. For developer messages, only type text is supported.

        • text: string

          The text content.

        • type: "text"

          The type of the content part.

          • "text"

        • prompt_cache_breakpoint: optional object { mode }

          Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.

          • mode: "explicit"

            The breakpoint mode. Always explicit.

            • "explicit"

    • role: "developer"

      The role of the messages author, in this case developer.

      • "developer"

    • name: optional string

      An optional name for the participant. Provides the model information to differentiate between participants of the same role.

  • ChatCompletionSystemMessageParam object { content, role, name }

    Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, use developer messages for this purpose instead.

    • content: string or array of ChatCompletionContentPartText

      The contents of the system message.

      • TextContent = string

        The contents of the system message.

      • ArrayOfContentParts = array of ChatCompletionContentPartText

        An array of content parts with a defined type. For system messages, only type text is supported.

        • text: string

          The text content.

        • type: "text"

          The type of the content part.

        • prompt_cache_breakpoint: optional object { mode }

          Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.

    • role: "system"

      The role of the messages author, in this case system.

      • "system"

    • name: optional string

      An optional name for the participant. Provides the model information to differentiate between participants of the same role.

  • ChatCompletionUserMessageParam object { content, role, name }

    Messages sent by an end user, containing prompts or additional context information.

    • content: string or array of ChatCompletionContentPart

      The contents of the user message.

      • TextContent = string

        The text contents of the message.

      • ArrayOfContentParts = array of ChatCompletionContentPart

        An array of content parts with a defined type. Supported options differ based on the model being used to generate the response. Can contain text, image, or audio inputs.

        • ChatCompletionContentPartText object { text, type, prompt_cache_breakpoint }

          Learn about text inputs.

          • text: string

            The text content.

          • type: "text"

            The type of the content part.

          • prompt_cache_breakpoint: optional object { mode }

            Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.

        • ChatCompletionContentPartImage object { image_url, type, prompt_cache_breakpoint }

          Learn about image inputs.

          • image_url: object { url, detail }

            • url: string

              Either a URL of the image or the base64 encoded image data.

            • detail: optional "auto" or "low" or "high"

              Specifies the detail level of the image. Learn more in the Vision guide.

              • "auto"

              • "low"

              • "high"

          • type: "image_url"

            The type of the content part.

            • "image_url"

          • prompt_cache_breakpoint: optional object { mode }

            Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.

            • mode: "explicit"

              The breakpoint mode. Always explicit.

              • "explicit"

        • ChatCompletionContentPartInputAudio object { input_audio, type, prompt_cache_breakpoint }

          Learn about audio inputs.

          • input_audio: object { data, format }

            • data: string

              Base64 encoded audio data.

            • format: "wav" or "mp3"

              The format of the encoded audio data. Currently supports "wav" and "mp3".

              • "wav"

              • "mp3"

          • type: "input_audio"

            The type of the content part. Always input_audio.

            • "input_audio"

          • prompt_cache_breakpoint: optional object { mode }

            Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.

            • mode: "explicit"

              The breakpoint mode. Always explicit.

              • "explicit"

        • FileContentPart object { file, type, prompt_cache_breakpoint }

          Learn about file inputs for text generation.

          • file: object { file_data, file_id, filename }

            • file_data: optional string

              The base64 encoded file data, used when passing the file to the model as a string.

            • file_id: optional string

              The ID of an uploaded file to use as input.

            • filename: optional string

              The name of the file, used when passing the file to the model as a string.

          • type: "file"

            The type of the content part. Always file.

            • "file"

          • prompt_cache_breakpoint: optional object { mode }

            Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.

            • mode: "explicit"

              The breakpoint mode. Always explicit.

              • "explicit"

    • role: "user"

      The role of the messages author, in this case user.

      • "user"

    • name: optional string

      An optional name for the participant. Provides the model information to differentiate between participants of the same role.

  • ChatCompletionAssistantMessageParam object { role, audio, content, 4 more }

    Messages sent by the model in response to user messages.

    • role: "assistant"

      The role of the messages author, in this case assistant.

      • "assistant"

    • audio: optional object { id } or null

      Data about a previous audio response from the model. Learn more.

      • id: string

        Unique identifier for a previous audio response from the model.

    • content: optional string or array of ChatCompletionContentPartText or ChatCompletionContentPartRefusal or null

      The contents of the assistant message. Required unless tool_calls or function_call is specified.

      • TextContent = string

        The contents of the assistant message.

      • ArrayOfContentParts = array of ChatCompletionContentPartText or ChatCompletionContentPartRefusal

        An array of content parts with a defined type. Can be one or more of type text, or exactly one of type refusal.

        • ChatCompletionContentPartText object { text, type, prompt_cache_breakpoint }

          Learn about text inputs.

        • ChatCompletionContentPartRefusal object { refusal, type }

          • refusal: string

            The refusal message generated by the model.

          • type: "refusal"

            The type of the content part.

            • "refusal"

    • function_call: optional object { arguments, name } or null

      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.

    • name: optional string

      An optional name for the participant. Provides the model information to differentiate between participants of the same role.

    • refusal: optional string or null

      The refusal message by the assistant.

    • tool_calls: optional array of ChatCompletionMessageToolCall

      The tool calls generated by the model, such as function calls.

      • ChatCompletionMessageFunctionToolCall object { id, function, type }

        A call to a function tool created by the model.

        • id: string

          The ID of the tool call.

        • function: object { arguments, name }

          The function that the model called.

          • 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.

        • type: "function"

          The type of the tool. Currently, only function is supported.

          • "function"

      • ChatCompletionMessageCustomToolCall object { id, custom, type }

        A call to a custom tool created by the model.

        • id: string

          The ID of the tool call.

        • custom: object { input, name }

          The custom tool that the model called.

          • input: string

            The input for the custom tool call generated by the model.

          • name: string

            The name of the custom tool to call.

        • type: "custom"

          The type of the tool. Always custom.

          • "custom"

  • ChatCompletionToolMessageParam object { content, role, tool_call_id }

    • content: string or array of ChatCompletionContentPartText

      The contents of the tool message.

      • TextContent = string

        The contents of the tool message.

      • ArrayOfContentParts = array of ChatCompletionContentPartText

        An array of content parts with a defined type. For tool messages, only type text is supported.

        • text: string

          The text content.

        • type: "text"

          The type of the content part.

        • prompt_cache_breakpoint: optional object { mode }

          Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.

    • role: "tool"

      The role of the messages author, in this case tool.

      • "tool"

    • tool_call_id: string

      Tool call that this message is responding to.

  • ChatCompletionFunctionMessageParam object { content, name, role }

    • content: string or null

      The contents of the function message.

    • name: string

      The name of the function to call.

    • role: "function"

      The role of the messages author, in this case function.

      • "function"

• model: string or "gpt-5.6-sol" or "gpt-5.6-terra" or "gpt-5.6-luna" or 78 more

  Model ID used to generate the response, like gpt-4o or o3. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the model guide to browse and compare available models.

  • string

  • "gpt-5.6-sol" or "gpt-5.6-terra" or "gpt-5.6-luna" or 78 more

    Model ID used to generate the response, like gpt-4o or o3. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the model guide to browse and compare available models.

    • "gpt-5.6-sol"

    • "gpt-5.6-terra"

    • "gpt-5.6-luna"

    • "gpt-5.4"

    • "gpt-5.4-mini"

    • "gpt-5.4-nano"

    • "gpt-5.4-mini-2026-03-17"

    • "gpt-5.4-nano-2026-03-17"

    • "gpt-5.3-chat-latest"

    • "gpt-5.2"

    • "gpt-5.2-2025-12-11"

    • "gpt-5.2-chat-latest"

    • "gpt-5.2-pro"

    • "gpt-5.2-pro-2025-12-11"

    • "gpt-5.1"

    • "gpt-5.1-2025-11-13"

    • "gpt-5.1-codex"

    • "gpt-5.1-mini"

    • "gpt-5.1-chat-latest"

    • "gpt-5"

    • "gpt-5-mini"

    • "gpt-5-nano"

    • "gpt-5-2025-08-07"

    • "gpt-5-mini-2025-08-07"

    • "gpt-5-nano-2025-08-07"

    • "gpt-5-chat-latest"

    • "gpt-4.1"

    • "gpt-4.1-mini"

    • "gpt-4.1-nano"

    • "gpt-4.1-2025-04-14"

    • "gpt-4.1-mini-2025-04-14"

    • "gpt-4.1-nano-2025-04-14"

    • "o4-mini"

    • "o4-mini-2025-04-16"

    • "o3"

    • "o3-2025-04-16"

    • "o3-mini"

    • "o3-mini-2025-01-31"

    • "o1"

    • "o1-2024-12-17"

    • "o1-preview"

    • "o1-preview-2024-09-12"

    • "o1-mini"

    • "o1-mini-2024-09-12"

    • "gpt-4o"

    • "gpt-4o-2024-11-20"

    • "gpt-4o-2024-08-06"

    • "gpt-4o-2024-05-13"

    • "gpt-4o-audio-preview"

    • "gpt-4o-audio-preview-2024-10-01"

    • "gpt-4o-audio-preview-2024-12-17"

    • "gpt-4o-audio-preview-2025-06-03"

    • "gpt-4o-mini-audio-preview"

    • "gpt-4o-mini-audio-preview-2024-12-17"

    • "gpt-4o-search-preview"

    • "gpt-4o-mini-search-preview"

    • "gpt-4o-search-preview-2025-03-11"

    • "gpt-4o-mini-search-preview-2025-03-11"

    • "chatgpt-4o-latest"

    • "codex-mini-latest"

    • "gpt-4o-mini"

    • "gpt-4o-mini-2024-07-18"

    • "gpt-4-turbo"

    • "gpt-4-turbo-2024-04-09"

    • "gpt-4-0125-preview"

    • "gpt-4-turbo-preview"

    • "gpt-4-1106-preview"

    • "gpt-4-vision-preview"

    • "gpt-4"

    • "gpt-4-0314"

    • "gpt-4-0613"

    • "gpt-4-32k"

    • "gpt-4-32k-0314"

    • "gpt-4-32k-0613"

    • "gpt-3.5-turbo"

    • "gpt-3.5-turbo-16k"

    • "gpt-3.5-turbo-0301"

    • "gpt-3.5-turbo-0613"

    • "gpt-3.5-turbo-1106"

    • "gpt-3.5-turbo-0125"

    • "gpt-3.5-turbo-16k-0613"

• audio: optional ChatCompletionAudioParam or null

  Parameters for audio output. Required when audio output is requested with modalities: ["audio"]. Learn more.

  • format: "wav" or "aac" or "mp3" or 3 more

    Specifies the output audio format. Must be one of wav, mp3, flac, opus, or pcm16.

    • "wav"

    • "aac"

    • "mp3"

    • "flac"

    • "opus"

    • "pcm16"

  • voice: string or "alloy" or "ash" or "ballad" or 7 more or object { id }

    The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }.

    • string

    • "alloy" or "ash" or "ballad" or 7 more

      • "alloy"

      • "ash"

      • "ballad"

      • "coral"

      • "echo"

      • "sage"

      • "shimmer"

      • "verse"

      • "marin"

      • "cedar"

    • ID object { id }

      Custom voice reference.

      • id: string

        The custom voice ID, e.g. voice_1234.

• frequency_penalty: optional number or null

  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.

• function_call: optional "none" or "auto" or ChatCompletionFunctionCallOption

  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" or "auto"

    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.

    • "none"

    • "auto"

  • ChatCompletionFunctionCallOption object { name }

    Specifying a particular function via {"name": "my_function"} forces the model to call that function.

    • name: string

      The name of the function to call.

• functions: optional array of object { name, description, parameters }

  Deprecated in favor of tools.

  A list of functions the model may generate JSON inputs for.

  • name: string

    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.

  • description: optional string

    A description of what the function does, used by the model to choose when and how to call the function.

  • parameters: optional FunctionParameters

    The parameters the functions accepts, described as a JSON Schema object. See the guide for examples, and the JSON Schema reference for documentation about the format.

    Omitting parameters defines a function with an empty parameter list.

• logit_bias: optional map[number] or null

  Modify the likelihood of specified tokens appearing in the completion.

  Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.

• logprobs: optional boolean or null

  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.

• max_completion_tokens: optional number or null

  An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and reasoning tokens.

• max_tokens: optional number or null

  The maximum number of tokens that can be generated in the chat completion. This value can be used to control costs for text generated via API.

  This value is now deprecated in favor of max_completion_tokens, and is not compatible with o-series models.

• metadata: optional Metadata or null

  Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

  Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

• modalities: optional array of "text" or "audio" or null

  Output types that you would like the model to generate. Most models are capable of generating text, which is the default:

  ["text"]

  The gpt-4o-audio-preview model can also be used to generate audio. To request that this model generate both text and audio responses, you can use:

  ["text", "audio"]

  • "text"

  • "audio"

• moderation: optional object { model, policy } or null

  Configuration for running moderation on the request input and generated output.

  • model: string

    The moderation model to use for moderated completions, e.g. 'omni-moderation-latest'.

  • policy: optional object { input, output } or null

    The policy to apply to moderated response input and output.

    • input: optional object { mode } or null

      The moderation policy for the response input.

      • mode: "score" or "block"

        • "score"

        • "block"

    • output: optional object { mode } or null

      The moderation policy for the response output.

      • mode: "score" or "block"

        • "score"

        • "block"

• n: optional number or null

  How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs.

• parallel_tool_calls: optional boolean

  Whether to enable parallel function calling during tool use.

• prediction: optional ChatCompletionPredictionContent or null

  Static predicted output content, such as the content of a text file that is being regenerated.

  • content: string or array of ChatCompletionContentPartText

    The content that should be matched when generating a model response. If generated tokens would match this content, the entire model response can be returned much more quickly.

    • TextContent = string

      The content used for a Predicted Output. This is often the text of a file you are regenerating with minor changes.

    • ArrayOfContentParts = array of ChatCompletionContentPartText

      An array of content parts with a defined type. Supported options differ based on the model being used to generate the response. Can contain text inputs.

      • text: string

        The text content.

      • type: "text"

        The type of the content part.

      • prompt_cache_breakpoint: optional object { mode }

        Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.

  • type: "content"

    The type of the predicted content you want to provide. This type is currently always content.

    • "content"

• presence_penalty: optional number or null

  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.

• prompt_cache_key: optional string or null

  Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces the user field. Learn more.

• prompt_cache_options: optional object { mode, ttl }

  Options for prompt caching. Supported for gpt-5.6 and later models. By default, OpenAI automatically chooses one implicit cache breakpoint. You can add explicit breakpoints to content blocks with prompt_cache_breakpoint. Each request can write up to four breakpoints. For cache matching, OpenAI considers up to the latest 80 breakpoints in the conversation, without a content-block lookback limit. Set mode to explicit to disable the implicit breakpoint. The ttl defaults to 30m, which is currently the only supported value. See the prompt caching guide for current details.

  • mode: optional "implicit" or "explicit"

    Controls whether OpenAI automatically creates an implicit cache breakpoint. Defaults to implicit. With implicit, OpenAI creates one implicit breakpoint and writes up to the latest three explicit breakpoints in the request. With explicit, OpenAI does not create an implicit breakpoint and writes up to the latest four explicit breakpoints. If there are no explicit breakpoints, the request does not use prompt caching.

    • "implicit"

    • "explicit"

  • ttl: optional "30m"

    The minimum lifetime applied to every implicit and explicit cache breakpoint written by the request. Defaults to 30m, which is currently the only supported value. The backend may retain cache entries for longer.

    • "30m"

• prompt_cache_retention: optional "in_memory" or "24h" or null

  Deprecated. Use prompt_cache_options.ttl instead.

  The retention policy for the prompt cache. Set to 24h to enable extended prompt caching, which keeps cached prefixes active for longer, up to a maximum of 24 hours. Learn more. This field expresses a maximum retention policy, while prompt_cache_options.ttl expresses a minimum cache lifetime. The two fields are independent and do not interact. For gpt-5.5, gpt-5.5-pro, and future models, only 24h is supported.

  For older models that support both in_memory and 24h, the default depends on your organization's data retention policy:

  • Organizations without ZDR enabled default to 24h.

  • Organizations with ZDR enabled default to in_memory when prompt_cache_retention is not specified.

  • "in_memory"

  • "24h"

• reasoning_effort: optional ReasoningEffort or null

  Constrains effort on reasoning for reasoning models. Currently supported values are none, minimal, low, medium, high, xhigh, and max. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response. Not all reasoning models support every value. See the reasoning guide for model-specific support.

  • "none"

  • "minimal"

  • "low"

  • "medium"

  • "high"

  • "xhigh"

  • "max"

• response_format: optional ResponseFormatText or ResponseFormatJSONSchema or ResponseFormatJSONObject

  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. Learn more in the Structured Outputs guide.

  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 object { type }

    Default response format. Used to generate text responses.

    • type: "text"

      The type of response format being defined. Always text.

      • "text"

  • ResponseFormatJSONSchema object { json_schema, type }

    JSON Schema response format. Used to generate structured JSON responses. Learn more about Structured Outputs.

    • json_schema: object { name, description, schema, strict }

      Structured Outputs configuration options, including a JSON Schema.

      • name: string

        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.

      • description: optional string

        A description of what the response format is for, used by the model to determine how to respond in the format.

      • schema: optional map[unknown]

        The schema for the response format, described as a JSON Schema object. Learn how to build JSON schemas here.

      • strict: optional boolean or null

        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. To learn more, read the Structured Outputs guide.

    • type: "json_schema"

      The type of response format being defined. Always json_schema.

      • "json_schema"

  • ResponseFormatJSONObject object { type }

    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"

      The type of response format being defined. Always json_object.

      • "json_object"

• safety_identifier: optional string or null

  A stable identifier used to help detect users of your application that may be violating OpenAI's usage policies. The IDs should be a string that uniquely identifies each user, with a maximum length of 64 characters. We recommend hashing their username or email address, in order to avoid sending us any identifying information. Learn more.

• seed: optional number or null

  This feature is in Beta. 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: optional "auto" or "default" or "flex" or 3 more or null

  Specifies the processing type used for serving the request.

  • If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'.
  • If set to 'default', then the request will be processed with the standard pricing and performance for the selected model.
  • If set to 'flex', then the request will be processed with the Flex Processing service tier.
  • To opt-in to Fast mode at the request level, include the service_tier=fast or service_tier=priority parameter for Responses or Chat Completions. The response will show service_tier=priority regardless of if you specify service_tier=fast or priority in your request.
  • When not set, the default behavior is 'auto'.

  When the service_tier parameter is set, the response body will include the service_tier value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter.

  • "auto"

  • "default"

  • "flex"

  • "scale"

  • "priority"

  • "fast"

• stop: optional string or array of string or null

  Not supported with latest reasoning models o3 and o4-mini.

  Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.

  • string

  • array of string

• store: optional boolean or null

  Whether or not to store the output of this chat completion request for use in our model distillation or evals products.

  Supports text and image inputs. Note: image inputs over 8MB will be dropped.

• stream: optional boolean or null

  If set to true, the model response data will be streamed to the client as it is generated using server-sent events. See the Streaming section below for more information, along with the streaming responses guide for more information on how to handle the streaming events.

• stream_options: optional ChatCompletionStreamOptions or null

  Options for streaming response. Only set this when you set stream: true.

  • include_obfuscation: optional boolean

    When true, stream obfuscation will be enabled. Stream obfuscation adds random characters to an obfuscation field on streaming delta events to normalize payload sizes as a mitigation to certain side-channel attacks. These obfuscation fields are included by default, but add a small amount of overhead to the data stream. You can set include_obfuscation to false to optimize for bandwidth if you trust the network links between your application and the OpenAI API.

  • include_usage: optional boolean

    If set, an additional chunk will be streamed before the data: [DONE] message. The usage field on this chunk shows the token usage statistics for the entire request, and the choices field will always be an empty array.

    All other chunks will also include a usage field, but with a null value. NOTE: If the stream is interrupted, you may not receive the final usage chunk which contains the total token usage for the request.

• temperature: optional number or null

  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.

• tool_choice: optional ChatCompletionToolChoiceOption

  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.

  • ToolChoiceMode = "none" or "auto" or "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. required means the model must call one or more tools.

    • "none"

    • "auto"

    • "required"

  • ChatCompletionAllowedToolChoice object { allowed_tools, type }

    Constrains the tools available to the model to a pre-defined set.

    • allowed_tools: ChatCompletionAllowedTools

      Constrains the tools available to the model to a pre-defined set.

      • mode: "auto" or "required"

        Constrains the tools available to the model to a pre-defined set.

        auto allows the model to pick from among the allowed tools and generate a message.

        required requires the model to call one or more of the allowed tools.

        • "auto"

        • "required"

      • tools: array of map[unknown]

        A list of tool definitions that the model should be allowed to call.

        For the Chat Completions API, the list of tool definitions might look like:

        [
          { "type": "function", "function": { "name": "get_weather" } },
          { "type": "function", "function": { "name": "get_time" } }
        ]
        

    • type: "allowed_tools"

      Allowed tool configuration type. Always allowed_tools.

      • "allowed_tools"

  • ChatCompletionNamedToolChoice object { function, type }

    Specifies a tool the model should use. Use to force the model to call a specific function.

    • function: object { name }

      • name: string

        The name of the function to call.

    • type: "function"

      For function calling, the type is always function.

      • "function"

  • ChatCompletionNamedToolChoiceCustom object { custom, type }

    Specifies a tool the model should use. Use to force the model to call a specific custom tool.

    • custom: object { name }

      • name: string

        The name of the custom tool to call.

    • type: "custom"

      For custom tool calling, the type is always custom.

      • "custom"

• tools: optional array of ChatCompletionTool

  A list of tools the model may call. You can provide either custom tools or function tools.

  • ChatCompletionFunctionTool object { function, type }

    A function tool that can be used to generate a response.

    • function: FunctionDefinition

      • name: string

        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.

      • description: optional string

        A description of what the function does, used by the model to choose when and how to call the function.

      • parameters: optional FunctionParameters

        The parameters the functions accepts, described as a JSON Schema object. See the guide for examples, and the JSON Schema reference for documentation about the format.

        Omitting parameters defines a function with an empty parameter list.

      • strict: optional boolean or null

        Whether to enable strict schema adherence when generating the function call. If set to true, the model will follow the exact schema defined in the parameters field. Only a subset of JSON Schema is supported when strict is true. Learn more about Structured Outputs in the function calling guide.

    • type: "function"

      The type of the tool. Currently, only function is supported.

      • "function"

  • ChatCompletionCustomTool object { custom, type }

    A custom tool that processes input using a specified format.

    • custom: object { name, description, format }

      Properties of the custom tool.

      • name: string

        The name of the custom tool, used to identify it in tool calls.

      • description: optional string

        Optional description of the custom tool, used to provide more context.

      • format: optional object { type } or object { grammar, type }

        The input format for the custom tool. Default is unconstrained text.

        • Text object { type }

          Unconstrained free-form text.

          • type: "text"

            Unconstrained text format. Always text.

            • "text"

        • Grammar object { grammar, type }

          A grammar defined by the user.

          • grammar: object { definition, syntax }

            Your chosen grammar.

            • definition: string

              The grammar definition.

            • syntax: "lark" or "regex"

              The syntax of the grammar definition. One of lark or regex.

              • "lark"

              • "regex"

          • type: "grammar"

            Grammar format. Always grammar.

            • "grammar"

    • type: "custom"

      The type of the custom tool. Always custom.

      • "custom"

• top_logprobs: optional number or null

  An integer between 0 and 20 specifying the maximum number of most likely tokens to return at each token position, each with an associated log probability. In some cases, the number of returned tokens may be fewer than requested. logprobs must be set to true if this parameter is used.

• top_p: optional number or null

  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.

• user: optional string

  This field is being replaced by safety_identifier and prompt_cache_key. Use prompt_cache_key instead to maintain caching optimizations. A stable identifier for your end-users. Used to boost cache hit rates by better bucketing similar requests and to help OpenAI detect and prevent abuse. Learn more.

• verbosity: optional "low" or "medium" or "high" or null

  Constrains the verbosity of the model's response. Lower values will result in more concise responses, while higher values will result in more verbose responses. Currently supported values are low, medium, and high. The default is medium.

  • "low"

  • "medium"

  • "high"

• web_search_options: optional object { search_context_size, user_location }

  This tool searches the web for relevant results to use in a response. Learn more about the web search tool.

  • search_context_size: optional "low" or "medium" or "high"

    High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

    • "low"

    • "medium"

    • "high"

  • user_location: optional object { approximate, type } or null

    Approximate location parameters for the search.

    • approximate: object { city, country, region, timezone }

      Approximate location parameters for the search.

      • city: optional string

        Free text input for the city of the user, e.g. San Francisco.

      • country: optional string

        The two-letter ISO country code of the user, e.g. US.

      • region: optional string

        Free text input for the region of the user, e.g. California.

      • timezone: optional string

        The IANA timezone of the user, e.g. America/Los_Angeles.

    • type: "approximate"

      The type of location approximation. Always approximate.

      • "approximate"

Returns

• ChatCompletion object { id, choices, created, 6 more }

  Represents a chat completion response returned by model, based on the provided input.

  • id: string

    A unique identifier for the chat completion.

  • choices: array of object { finish_reason, index, logprobs, message }

    A list of chat completion choices. Can be more than one if n is greater than 1.

    • finish_reason: "stop" or "length" or "tool_calls" or 2 more

      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, content_filter if content was omitted due to a flag from our content filters, tool_calls if the model called a tool, or function_call (deprecated) if the model called a function. Read the Model Spec for more.

      • "stop"

      • "length"

      • "tool_calls"

      • "content_filter"

      • "function_call"

    • index: number

      The index of the choice in the list of choices.

    • logprobs: object { content, refusal } or null

      Log probability information for the choice.

      • content: array of ChatCompletionTokenLogprob or null

        A list of message content tokens with log probability information.

        • token: string

          The token.

        • bytes: array of number or null

          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.

        • logprob: number

          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.

        • top_logprobs: array of object { token, bytes, logprob }

          List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

          • token: string

            The token.

          • bytes: array of number or null

            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.

          • logprob: number

            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.

      • refusal: array of ChatCompletionTokenLogprob or null

        A list of message refusal tokens with log probability information.

        • token: string

          The token.

        • bytes: array of number or null

          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.

        • logprob: number

          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.

        • top_logprobs: array of object { token, bytes, logprob }

          List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

    • message: ChatCompletionMessage

      A chat completion message generated by the model.

      • content: string or null

        The contents of the message.

      • refusal: string or null

        The refusal message generated by the model.

      • role: "assistant"

        The role of the author of this message.

        • "assistant"

      • annotations: optional array of object { type, url_citation }

        Annotations for the message, when applicable, as when using the web search tool.

        • type: "url_citation"

          The type of the URL citation. Always url_citation.

          • "url_citation"

        • url_citation: object { end_index, start_index, title, url }

          A URL citation when using web search.

          • end_index: number

            The index of the last character of the URL citation in the message.

          • start_index: number

            The index of the first character of the URL citation in the message.

          • title: string

            The title of the web resource.

          • url: string

            The URL of the web resource.

      • audio: optional ChatCompletionAudio or null

        If the audio output modality is requested, this object contains data about the audio response from the model. Learn more.

        • id: string

          Unique identifier for this audio response.

        • data: string

          Base64 encoded audio bytes generated by the model, in the format specified in the request.

        • expires_at: number

          The Unix timestamp (in seconds) for when this audio response will no longer be accessible on the server for use in multi-turn conversations.

        • transcript: string

          Transcript of the audio generated by the model.

      • function_call: optional object { arguments, name }

        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.

      • tool_calls: optional array of ChatCompletionMessageToolCall

        The tool calls generated by the model, such as function calls.

        • ChatCompletionMessageFunctionToolCall object { id, function, type }

          A call to a function tool created by the model.

          • id: string

            The ID of the tool call.

          • function: object { arguments, name }

            The function that the model called.

            • 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.

          • type: "function"

            The type of the tool. Currently, only function is supported.

            • "function"

        • ChatCompletionMessageCustomToolCall object { id, custom, type }

          A call to a custom tool created by the model.

          • id: string

            The ID of the tool call.

          • custom: object { input, name }

            The custom tool that the model called.

            • input: string

              The input for the custom tool call generated by the model.

            • name: string

              The name of the custom tool to call.

          • type: "custom"

            The type of the tool. Always custom.

            • "custom"

  • created: number

    The Unix timestamp (in seconds) of when the chat completion was created.

  • model: string

    The model used for the chat completion.

  • object: "chat.completion"

    The object type, which is always chat.completion.

    • "chat.completion"

  • moderation: optional object { input, output } or null

    Moderation results for the request input and generated output, if moderated completions were requested.

    • input: object { model, results, type } or object { code, message, type }

      Moderation for the request input.

      • ModerationResults object { model, results, type }

        Successful moderation results for the request input or generated output.

        • model: string

          The moderation model used to generate the results.

        • results: array of object { categories, category_applied_input_types, category_scores, 3 more }

          A list of moderation results.

          • categories: map[boolean]

            A dictionary of moderation categories to booleans, True if the input is flagged under this category.

          • category_applied_input_types: map[array of "text" or "image"]

            Which modalities of input are reflected by the score for each category.

            • "text"

            • "image"

          • category_scores: map[number]

            A dictionary of moderation categories to scores.

          • flagged: boolean

            A boolean indicating whether the content was flagged by any category.

          • model: string

            The moderation model that produced this result.

          • type: "moderation_result"

            The object type, which was always moderation_result for successful moderation results.

            • "moderation_result"

        • type: "moderation_results"

          The object type, which is always moderation_results.

          • "moderation_results"

      • Error object { code, message, type }

        An error produced while attempting moderation.

        • code: string

          The error code.

        • message: string

          The error message.

        • type: "error"

          The object type, which is always error.

          • "error"

    • output: object { model, results, type } or object { code, message, type }

      Moderation for the generated output.

      • ModerationResults object { model, results, type }

        Successful moderation results for the request input or generated output.

        • model: string

          The moderation model used to generate the results.

        • results: array of object { categories, category_applied_input_types, category_scores, 3 more }

          A list of moderation results.

          • categories: map[boolean]

            A dictionary of moderation categories to booleans, True if the input is flagged under this category.

          • category_applied_input_types: map[array of "text" or "image"]

            Which modalities of input are reflected by the score for each category.

            • "text"

            • "image"

          • category_scores: map[number]

            A dictionary of moderation categories to scores.

          • flagged: boolean

            A boolean indicating whether the content was flagged by any category.

          • model: string

            The moderation model that produced this result.

          • type: "moderation_result"

            The object type, which was always moderation_result for successful moderation results.

            • "moderation_result"

        • type: "moderation_results"

          The object type, which is always moderation_results.

          • "moderation_results"

      • Error object { code, message, type }

        An error produced while attempting moderation.

        • code: string

          The error code.

        • message: string

          The error message.

        • type: "error"

          The object type, which is always error.

          • "error"

  • service_tier: optional "auto" or "default" or "flex" or 3 more or null

    Specifies the processing type used for serving the request.

    • If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'.
    • If set to 'default', then the request will be processed with the standard pricing and performance for the selected model.
    • If set to 'flex', then the request will be processed with the Flex Processing service tier.
    • To opt-in to Fast mode at the request level, include the service_tier=fast or service_tier=priority parameter for Responses or Chat Completions. The response will show service_tier=priority regardless of if you specify service_tier=fast or priority in your request.
    • When not set, the default behavior is 'auto'.

    When the service_tier parameter is set, the response body will include the service_tier value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter.

    • "auto"

    • "default"

    • "flex"

    • "scale"

    • "priority"

    • "fast"

  • system_fingerprint: optional 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.

  • usage: optional CompletionUsage

    Usage statistics for the completion request.

    • completion_tokens: number

      Number of tokens in the generated completion.

    • prompt_tokens: number

      Number of tokens in the prompt.

    • total_tokens: number

      Total number of tokens used in the request (prompt + completion).

    • completion_tokens_details: optional object { accepted_prediction_tokens, audio_tokens, reasoning_tokens, rejected_prediction_tokens }

      Breakdown of tokens used in a completion.

      • accepted_prediction_tokens: optional number

        When using Predicted Outputs, the number of tokens in the prediction that appeared in the completion.

      • audio_tokens: optional number

        Audio input tokens generated by the model.

      • reasoning_tokens: optional number

        Tokens generated by the model for reasoning.

      • rejected_prediction_tokens: optional number

        When using Predicted Outputs, the number of tokens in the prediction that did not appear in the completion. However, like reasoning tokens, these tokens are still counted in the total completion tokens for purposes of billing, output, and context window limits.

    • prompt_tokens_details: optional object { audio_tokens, cache_write_tokens, cached_tokens }

      Breakdown of tokens used in the prompt.

      • audio_tokens: optional number

        Audio input tokens present in the prompt.

      • cache_write_tokens: optional number

        The unadjusted number of prompt tokens written to cache.

      • cached_tokens: optional number

        Cached tokens present in the prompt.

Example

curl https://api.openai.com/v1/chat/completions \
    -H 'Content-Type: application/json' \
    -H "Authorization: Bearer $OPENAI_API_KEY" \
    -d '{
          "messages": [
            {
              "content": "string",
              "role": "developer"
            }
          ],
          "model": "gpt-5.4",
          "n": 1,
          "prompt_cache_key": "prompt-cache-key-1234",
          "safety_identifier": "safety-identifier-1234",
          "temperature": 1,
          "top_p": 1,
          "user": "user-1234"
        }'

Response

{
  "id": "id",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "logprobs": {
        "content": [
          {
            "token": "token",
            "bytes": [
              0
            ],
            "logprob": 0,
            "top_logprobs": [
              {
                "token": "token",
                "bytes": [
                  0
                ],
                "logprob": 0
              }
            ]
          }
        ],
        "refusal": [
          {
            "token": "token",
            "bytes": [
              0
            ],
            "logprob": 0,
            "top_logprobs": [
              {
                "token": "token",
                "bytes": [
                  0
                ],
                "logprob": 0
              }
            ]
          }
        ]
      },
      "message": {
        "content": "content",
        "refusal": "refusal",
        "role": "assistant",
        "annotations": [
          {
            "type": "url_citation",
            "url_citation": {
              "end_index": 0,
              "start_index": 0,
              "title": "title",
              "url": "https://example.com"
            }
          }
        ],
        "audio": {
          "id": "id",
          "data": "data",
          "expires_at": 0,
          "transcript": "transcript"
        },
        "function_call": {
          "arguments": "arguments",
          "name": "name"
        },
        "tool_calls": [
          {
            "id": "id",
            "function": {
              "arguments": "arguments",
              "name": "name"
            },
            "type": "function"
          }
        ]
      }
    }
  ],
  "created": 0,
  "model": "model",
  "object": "chat.completion",
  "moderation": {
    "input": {
      "model": "model",
      "results": [
        {
          "categories": {
            "foo": true
          },
          "category_applied_input_types": {
            "foo": [
              "text"
            ]
          },
          "category_scores": {
            "foo": 0
          },
          "flagged": true,
          "model": "model",
          "type": "moderation_result"
        }
      ],
      "type": "moderation_results"
    },
    "output": {
      "model": "model",
      "results": [
        {
          "categories": {
            "foo": true
          },
          "category_applied_input_types": {
            "foo": [
              "text"
            ]
          },
          "category_scores": {
            "foo": 0
          },
          "flagged": true,
          "model": "model",
          "type": "moderation_result"
        }
      ],
      "type": "moderation_results"
    }
  },
  "service_tier": "auto",
  "system_fingerprint": "system_fingerprint",
  "usage": {
    "completion_tokens": 0,
    "prompt_tokens": 0,
    "total_tokens": 0,
    "completion_tokens_details": {
      "accepted_prediction_tokens": 0,
      "audio_tokens": 0,
      "reasoning_tokens": 0,
      "rejected_prediction_tokens": 0
    },
    "prompt_tokens_details": {
      "audio_tokens": 0,
      "cache_write_tokens": 0,
      "cached_tokens": 0
    }
  }
}

Example

curl https://api.openai.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "VAR_chat_model_id",
    "messages": [
      {
        "role": "developer",
        "content": "You are a helpful assistant."
      },
      {
        "role": "user",
        "content": "Hello!"
      }
    ]
  }'

Response

{
  "id": "chatcmpl-B9MBs8CjcvOU2jLn4n570S5qMJKcT",
  "object": "chat.completion",
  "created": 1741569952,
  "model": "gpt-5.4",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! How can I assist you today?",
        "refusal": null,
        "annotations": []
      },
      "logprobs": null,
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 19,
    "completion_tokens": 10,
    "total_tokens": 29,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "audio_tokens": 0
    },
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "audio_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  },
  "service_tier": "default"
}

Functions

curl https://api.openai.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
  "model": "gpt-5.4",
  "messages": [
    {
      "role": "user",
      "content": "What is the weather like in Boston today?"
    }
  ],
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "get_current_weather",
        "description": "Get the current weather in a given location",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {
              "type": "string",
              "description": "The city and state, e.g. San Francisco, CA"
            },
            "unit": {
              "type": "string",
              "enum": ["celsius", "fahrenheit"]
            }
          },
          "required": ["location"]
        }
      }
    }
  ],
  "tool_choice": "auto"
}'

Response

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1699896916,
  "model": "gpt-4o-mini",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": null,
        "tool_calls": [
          {
            "id": "call_abc123",
            "type": "function",
            "function": {
              "name": "get_current_weather",
              "arguments": "{\n\"location\": \"Boston, MA\"\n}"
            }
          }
        ]
      },
      "logprobs": null,
      "finish_reason": "tool_calls"
    }
  ],
  "usage": {
    "prompt_tokens": 82,
    "completion_tokens": 17,
    "total_tokens": 99,
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  }
}

Image input

curl https://api.openai.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-5.4",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "What is in this image?"
          },
          {
            "type": "image_url",
            "image_url": {
              "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
            }
          }
        ]
      }
    ],
    "max_tokens": 300
  }'

Response

{
  "id": "chatcmpl-B9MHDbslfkBeAs8l4bebGdFOJ6PeG",
  "object": "chat.completion",
  "created": 1741570283,
  "model": "gpt-5.4",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "The image shows a wooden boardwalk path running through a lush green field or meadow. The sky is bright blue with some scattered clouds, giving the scene a serene and peaceful atmosphere. Trees and shrubs are visible in the background.",
        "refusal": null,
        "annotations": []
      },
      "logprobs": null,
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 1117,
    "completion_tokens": 46,
    "total_tokens": 1163,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "audio_tokens": 0
    },
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "audio_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  },
  "service_tier": "default"
}

Logprobs

curl https://api.openai.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "VAR_chat_model_id",
    "messages": [
      {
        "role": "user",
        "content": "Hello!"
      }
    ],
    "logprobs": true,
    "top_logprobs": 2
  }'

Response

{
  "id": "chatcmpl-123",
  "object": "chat.completion",
  "created": 1702685778,
  "model": "gpt-4o-mini",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! How can I assist you today?"
      },
      "logprobs": {
        "content": [
          {
            "token": "Hello",
            "logprob": -0.31725305,
            "bytes": [72, 101, 108, 108, 111],
            "top_logprobs": [
              {
                "token": "Hello",
                "logprob": -0.31725305,
                "bytes": [72, 101, 108, 108, 111]
              },
              {
                "token": "Hi",
                "logprob": -1.3190403,
                "bytes": [72, 105]
              }
            ]
          },
          {
            "token": "!",
            "logprob": -0.02380986,
            "bytes": [
              33
            ],
            "top_logprobs": [
              {
                "token": "!",
                "logprob": -0.02380986,
                "bytes": [33]
              },
              {
                "token": " there",
                "logprob": -3.787621,
                "bytes": [32, 116, 104, 101, 114, 101]
              }
            ]
          },
          {
            "token": " How",
            "logprob": -0.000054669687,
            "bytes": [32, 72, 111, 119],
            "top_logprobs": [
              {
                "token": " How",
                "logprob": -0.000054669687,
                "bytes": [32, 72, 111, 119]
              },
              {
                "token": "<|end|>",
                "logprob": -10.953937,
                "bytes": null
              }
            ]
          },
          {
            "token": " can",
            "logprob": -0.015801601,
            "bytes": [32, 99, 97, 110],
            "top_logprobs": [
              {
                "token": " can",
                "logprob": -0.015801601,
                "bytes": [32, 99, 97, 110]
              },
              {
                "token": " may",
                "logprob": -4.161023,
                "bytes": [32, 109, 97, 121]
              }
            ]
          },
          {
            "token": " I",
            "logprob": -3.7697225e-6,
            "bytes": [
              32,
              73
            ],
            "top_logprobs": [
              {
                "token": " I",
                "logprob": -3.7697225e-6,
                "bytes": [32, 73]
              },
              {
                "token": " assist",
                "logprob": -13.596657,
                "bytes": [32, 97, 115, 115, 105, 115, 116]
              }
            ]
          },
          {
            "token": " assist",
            "logprob": -0.04571125,
            "bytes": [32, 97, 115, 115, 105, 115, 116],
            "top_logprobs": [
              {
                "token": " assist",
                "logprob": -0.04571125,
                "bytes": [32, 97, 115, 115, 105, 115, 116]
              },
              {
                "token": " help",
                "logprob": -3.1089056,
                "bytes": [32, 104, 101, 108, 112]
              }
            ]
          },
          {
            "token": " you",
            "logprob": -5.4385737e-6,
            "bytes": [32, 121, 111, 117],
            "top_logprobs": [
              {
                "token": " you",
                "logprob": -5.4385737e-6,
                "bytes": [32, 121, 111, 117]
              },
              {
                "token": " today",
                "logprob": -12.807695,
                "bytes": [32, 116, 111, 100, 97, 121]
              }
            ]
          },
          {
            "token": " today",
            "logprob": -0.0040071653,
            "bytes": [32, 116, 111, 100, 97, 121],
            "top_logprobs": [
              {
                "token": " today",
                "logprob": -0.0040071653,
                "bytes": [32, 116, 111, 100, 97, 121]
              },
              {
                "token": "?",
                "logprob": -5.5247097,
                "bytes": [63]
              }
            ]
          },
          {
            "token": "?",
            "logprob": -0.0008108172,
            "bytes": [63],
            "top_logprobs": [
              {
                "token": "?",
                "logprob": -0.0008108172,
                "bytes": [63]
              },
              {
                "token": "?\n",
                "logprob": -7.184561,
                "bytes": [63, 10]
              }
            ]
          }
        ]
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 9,
    "completion_tokens": 9,
    "total_tokens": 18,
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  },
  "system_fingerprint": null
}

Streaming

curl https://api.openai.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "VAR_chat_model_id",
    "messages": [
      {
        "role": "developer",
        "content": "You are a helpful assistant."
      },
      {
        "role": "user",
        "content": "Hello!"
      }
    ],
    "stream": true
  }'

Response

{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini", "system_fingerprint": "fp_44709d6fcb", "choices":[{"index":0,"delta":{"role":"assistant","content":""},"logprobs":null,"finish_reason":null}]}

{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini", "system_fingerprint": "fp_44709d6fcb", "choices":[{"index":0,"delta":{"content":"Hello"},"logprobs":null,"finish_reason":null}]}

....

{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini", "system_fingerprint": "fp_44709d6fcb", "choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}]}