OpenAI models#

LLM ships with a default plugin for talking to OpenAI’s API. OpenAI offer both language models and embedding models, and LLM can access both types.

Configuration#

All OpenAI models are accessed using an API key. You can obtain one from the API keys page on their site.

Once you have created a key, configure LLM to use it by running:

llm keys set openai

Then paste in the API key.

OpenAI language models#

Run llm models for a full list of available models. The OpenAI models supported by LLM are:

OpenAI Chat: gpt-4o (aliases: 4o)
OpenAI Chat: chatgpt-4o-latest (aliases: chatgpt-4o)
OpenAI Chat: gpt-4o-mini (aliases: 4o-mini)
OpenAI Chat: gpt-4o-audio-preview
OpenAI Chat: gpt-4o-audio-preview-2024-12-17
OpenAI Chat: gpt-4o-audio-preview-2024-10-01
OpenAI Chat: gpt-4o-mini-audio-preview
OpenAI Chat: gpt-4o-mini-audio-preview-2024-12-17
OpenAI Chat: gpt-4.1 (aliases: 4.1)
OpenAI Chat: gpt-4.1-mini (aliases: 4.1-mini)
OpenAI Chat: gpt-4.1-nano (aliases: 4.1-nano)
OpenAI Chat: gpt-3.5-turbo (aliases: 3.5, chatgpt)
OpenAI Chat: gpt-3.5-turbo-16k (aliases: chatgpt-16k, 3.5-16k)
OpenAI Chat: gpt-4 (aliases: 4, gpt4)
OpenAI Chat: gpt-4-32k (aliases: 4-32k)
OpenAI Chat: gpt-4-1106-preview
OpenAI Chat: gpt-4-0125-preview
OpenAI Chat: gpt-4-turbo-2024-04-09
OpenAI Chat: gpt-4-turbo (aliases: gpt-4-turbo-preview, 4-turbo, 4t)
OpenAI Chat: gpt-4.5-preview-2025-02-27
OpenAI Chat: gpt-4.5-preview (aliases: gpt-4.5)
OpenAI Chat: o1
OpenAI Chat: o1-2024-12-17
OpenAI Chat: o1-preview
OpenAI Chat: o1-mini
OpenAI Chat: o3-mini
OpenAI Chat: o3
OpenAI Chat: o4-mini
OpenAI Completion: gpt-3.5-turbo-instruct (aliases: 3.5-instruct, chatgpt-instruct)

See the OpenAI models documentation for details of each of these.

gpt-4o-mini (aliased to 4o-mini) is the least expensive model, and is the default for if you don’t specify a model at all. Consult OpenAI’s model documentation for details of the other models.

o1-pro is not available through the Chat Completions API used by LLM’s default OpenAI plugin. You can install the new llm-openai-plugin plugin to access that model.

Model features#

The following features work with OpenAI models:

  • System prompts can be used to provide instructions that have a higher weight than the prompt itself.

  • Attachments. Many OpenAI models support image inputs - check which ones using llm models --options. Any model that accepts images can also accept PDFs.

  • Schemas can be used to influence the JSON structure of the model output.

  • Model options can be used to set parameters like temperature. Use llm models --options for a full list of supported options.

OpenAI embedding models#

Run llm embed-models for a list of embedding models. The following OpenAI embedding models are supported by LLM:

ada-002 (aliases: ada, oai)
3-small
3-large
3-small-512
3-large-256
3-large-1024

The 3-small model is currently the most inexpensive. 3-large costs more but is more capable - see New embedding models and API updates on the OpenAI blog for details and benchmarks.

An important characteristic of any embedding model is the size of the vector it returns. Smaller vectors cost less to store and query, but may be less accurate.

OpenAI 3-small and 3-large vectors can be safely truncated to lower dimensions without losing too much accuracy. The -int models provided by LLM are pre-configured to do this, so 3-large-256 is the 3-large model truncated to 256 dimensions.

The vector size of the supported OpenAI embedding models are as follows:

Model

Size

ada-002

1536

3-small

1536

3-large

3072

3-small-512

512

3-large-256

256

3-large-1024

1024

OpenAI completion models#

The gpt-3.5-turbo-instruct model is a little different - it is a completion model rather than a chat model, described in the OpenAI completions documentation.

Completion models can be called with the -o logprobs 3 option (not supported by chat models) which will cause LLM to store 3 log probabilities for each returned token in the SQLite database. Consult this issue for details on how to read these values.

Adding more OpenAI models#

OpenAI occasionally release new models with new names. LLM aims to ship new releases to support these, but you can also configure them directly, by adding them to a extra-openai-models.yaml configuration file.

Run this command to find the directory in which this file should be created:

dirname "$(llm logs path)"

On my Mac laptop I get this:

~/Library/Application Support/io.datasette.llm

Create a file in that directory called extra-openai-models.yaml.

Let’s say OpenAI have just released the gpt-3.5-turbo-0613 model and you want to use it, despite LLM not yet shipping support. You could configure that by adding this to the file:

- model_id: gpt-3.5-turbo-0613
  model_name: gpt-3.5-turbo-0613
  aliases: ["0613"]

The model_id is the identifier that will be recorded in the LLM logs. You can use this to specify the model, or you can optionally include a list of aliases for that model. The model_name is the actual model identifier that will be passed to the API, which must match exactly what the API expects.

If the model is a completion model (such as gpt-3.5-turbo-instruct) add completion: true to the configuration.

If the model supports structured extraction using json_schema, add supports_schema: true to the configuration.

For reasoning models like o1 or o3-mini add reasoning: true.

With this configuration in place, the following command should run a prompt against the new model:

llm -m 0613 'What is the capital of France?'

Run llm models to confirm that the new model is now available:

llm models

Example output:

OpenAI Chat: gpt-3.5-turbo (aliases: 3.5, chatgpt)
OpenAI Chat: gpt-3.5-turbo-16k (aliases: chatgpt-16k, 3.5-16k)
OpenAI Chat: gpt-4 (aliases: 4, gpt4)
OpenAI Chat: gpt-4-32k (aliases: 4-32k)
OpenAI Chat: gpt-3.5-turbo-0613 (aliases: 0613)

Running llm logs -n 1 should confirm that the prompt and response has been correctly logged to the database.