Generate a completion Generate a chat completion List Local Models Show Model Information Generate Embeddings List Running Models Model names follow a model:tag format, where model can have an optional namespace such as example/model . Some examples are orca-mini:3b-q4_1 and llama3:70b . The tag is optional and, if not provided, will default to latest . The tag is used to identify a specific version. All durations are returned in nanoseconds. Streaming responses Certain endpoints stream responses as JSON objects. Streaming can be disabled by providing {"stream": false} for these endpoints. Generate a completion Generate a response for a given prompt with a provided model. This is a streaming endpoint, so there will be a series of responses. The final response object will include statistics and additional data from the request. model : (required) the model name prompt : the prompt to generate a response for suffix : the text after the model response images : (optional) a list of base64-encoded images (for multimodal models such as llava ) Advanced parameters (optional): format : the format to return a response in. Currently the only accepted value is json options : additional model parameters listed in the documentation for the Modelfile such as temperature system : system message to (overrides what is defined in the Modelfile ) template : the prompt template to use (overrides what is defined in the Modelfile ) context : the context parameter returned from a previous request to /generate , this can be used to keep a short conversational memory stream : if false the response will be returned as a single response object, rather than a stream of objects raw : if true no formatting will be applied to the prompt. You may choose to use the raw parameter if you are specifying a full templated prompt in your request to the API keep_alive : controls how long the model will stay loaded into memory following the request (default: 5m ) Enable JSON mode by setting the format parameter to json . This will structure the response as a valid JSON object. See the JSON mode example below. [!IMPORTANT] It's important to instruct the model to use JSON in the prompt . Otherwise, the model may generate large amounts whitespace. Generate request (Streaming) A stream of JSON objects is returned: The final response in the stream also includes additional data about the generation: total_duration : time spent generating the response load_duration : time spent in nanoseconds loading the model prompt_eval_count : number of tokens in the prompt prompt_eval_duration : time spent in nanoseconds evaluating the prompt eval_count : number of tokens in the response eval_duration : time in nanoseconds spent generating the response context : an encoding of the conversation used in this response, this can be sent in the next request to keep a conversational memory response : empty if the response was streamed, if not streamed, this will contain the full response To calculate how fast the response is generated in tokens per second (token/s), divide eval_count / eval_duration * 10^9 . Request (No streaming) A response can be received in one reply when streaming is off. If stream is set to false , the response will be a single JSON object: Request (with suffix) Request (JSON mode) [!IMPORTANT] When format is set to json , the output will always be a well-formed JSON object. It's important to also instruct the model to respond in JSON. The value of response will be a string containing JSON similar to: Request (with images) To submit images to multimodal models such as llava or bakllava , provide a list of base64-encoded images : Request (Raw Mode) In some cases, you may wish to bypass the templating system and provide a full prompt. In this case, you can use the raw parameter to disable templating. Also note that raw mode will not return a context. Request (Reproducible outputs) For reproducible outputs, set seed to a number: Generate request (With options) If you want to set custom options for the model at runtime rather than in the Modelfile, you can do so with the options parameter. This example sets every available option, but you can set any of them individually and omit the ones you do not want to override. If an empty prompt is provided, the model will be loaded into memory. A single JSON object is returned: If an empty prompt is provided and the keep_alive parameter is set to 0 , a model will be unloaded from memory. A single JSON object is returned: Generate a chat completion Generate the next message in a chat with a provided model. This is a streaming endpoint, so there will be a series of responses. Streaming can be disabled using "stream": false . The final response object will include statistics and additional data from the request. model : (required) the model name messages : the messages of the chat, this can be used to keep a chat memory tools : tools for the model to use if supported. Requires stream to be set to false The message object has the following fields: role : the role of the message, either system , user , assistant , or tool content : the content of the message images (optional): a list of images to include in the message (for multimodal models such as llava ) tool_calls (optional): a list of tools the model wants to use Advanced parameters (optional): format : the format to return a response in. Currently the only accepted value is json options : additional model parameters listed in the documentation for the Modelfile such as temperature stream : if false the response will be returned as a single response object, rather than a stream of objects keep_alive : controls how long the model will stay loaded into memory following the request (default: 5m ) Chat Request (Streaming) Send a chat message with a streaming response. A stream of JSON objects is returned: Final response: Chat request (No streaming) Chat request (With History) Send a chat message with a conversation history. You can use this same approach to start the conversation using multi-shot or chain-of-thought prompting.

A stream of JSON objects is returned: Final response: Chat request (with images) Send a chat message with images. The images should be provided as an array, with the individual images encoded in Base64. Chat request (Reproducible outputs) Chat request (with tools) If the messages array is empty, the model will be loaded into memory. If the messages array is empty and the keep_alive parameter is set to 0 , a model will be unloaded from memory. A single JSON object is returned: Create a model from a Modelfile . It is recommended to set modelfile to the content of the Modelfile rather than just set path . This is a requirement for remote create. Remote model creation must also create any file blobs, fields such as FROM and ADAPTER , explicitly with the server using Create a Blob and the value to the path indicated in the response. model : name of the model to create modelfile (optional): contents of the Modelfile stream : (optional) if false the response will be returned as a single response object, rather than a stream of objects path (optional): path to the Modelfile quantize (optional): quantize a non-quantized (e.g. float16) model Quantization types Create a new model Create a new model from a Modelfile . A stream of JSON objects is returned: Quantize a model Quantize a non-quantized model. A stream of JSON objects is returned: Check if a Blob Exists Ensures that the file blob used for a FROM or ADAPTER field exists on the server. This is checking your Ollama server and not ollama.com. Query Parameters digest : the SHA256 digest of the blob Return 200 OK if the blob exists, 404 Not Found if it does not. Create a blob from a file on the server. Returns the server file path. Query Parameters digest : the expected SHA256 digest of the file Return 201 Created if the blob was successfully created, 400 Bad Request if the digest used is not expected. List Local Models List models that are available locally. A single JSON object will be returned. Show Model Information Show information about a model including details, modelfile, template, parameters, license, system prompt. model : name of the model to show verbose : (optional) if set to true , returns full data for verbose response fields Copy a model. Creates a model with another name from an existing model. Returns a 200 OK if successful, or a 404 Not Found if the source model doesn't exist. Delete a model and its data. model : model name to delete Returns a 200 OK if successful, 404 Not Found if the model to be deleted doesn't exist. Download a model from the ollama library. Cancelled pulls are resumed from where they left off, and multiple calls will share the same download progress. model : name of the model to pull insecure : (optional) allow insecure connections to the library. Only use this if you are pulling from your own library during development. stream : (optional) if false the response will be returned as a single response object, rather than a stream of objects If stream is not specified, or set to true , a stream of JSON objects is returned: The first object is the manifest: Then there is a series of downloading responses. Until any of the download is completed, the completed key may not be included. The number of files to be downloaded depends on the number of layers specified in the manifest. After all the files are downloaded, the final responses are: if stream is set to false, then the response is a single JSON object: Upload a model to a model library. Requires registering for ollama.ai and adding a public key first. model : name of the model to push in the form of <namespace>/<model>:<tag> insecure : (optional) allow insecure connections to the library. Only use this if you are pushing to your library during development. stream : (optional) if false the response will be returned as a single response object, rather than a stream of objects If stream is not specified, or set to true , a stream of JSON objects is returned: Then there is a series of uploading responses: Finally, when the upload is complete: If stream is set to false , then the response is a single JSON object: Generate Embeddings Generate embeddings from a model model : name of model to generate embeddings from input : text or list of text to generate embeddings for Advanced parameters: truncate : truncates the end of each input to fit within context length. Returns error if false and context length is exceeded. Defaults to true options : additional model parameters listed in the documentation for the Modelfile such as temperature keep_alive : controls how long the model will stay loaded into memory following the request (default: 5m ) Request (Multiple input) List Running Models List models that are currently loaded into memory. A single JSON object will be returned. Generate Embedding Note: this endpoint has been superseded by /api/embed Generate embeddings from a model model : name of model to generate embeddings from prompt : text to generate embeddings for Advanced parameters: options : additional model parameters listed in the documentation for the Modelfile such as temperature keep_alive : controls how long the model will stay loaded into memory following the request (default: 5m )