Retool AI providers and models
Learn about the different AI providers and models that Retool supports.
AI providers use models that are trained on specific types of data to make relevant decisions and perform tasks. For example, you would interact with one type of model to generate chat responses and a different model to generate images. AI models are also known as LLMs (large language models).
In general, a model is a collective group of model instances, each of which vary in terms of functionality or data. For example, there are different instances of OpenAI's GPT-4 model, such as gpt-4 and gpt-4-turbo. You can specify the exact model instance when configuring Retool AI.
Retool supports a number of AI providers and their models for use with AI actions and agents.
AI tokens
Use OpenAI's tokenizer tool to calculate how many tokens would result from a passage of text.
AI models use tokens, rather than characters or bytes, to represent the commonality of sequences and usage. In general, a single token can equate to approximately four characters.
The text you provide in an AI query is converted by the model into tokens, after which it can generate the necessary response.
Retool-managed and self-managed models
LLM interactions work by making API requests with an AI provider. As with most other APIs, these requests require authorization credentials, such as an API key. Retool provides access to certain AI models using Retool-managed connections that use Retool's own API keys.
A Retool-managed LLM connection enables you to start building and testing with AI models straight away without needing any additional tools or services. Once you're ready to use your AI actions or agents in production, you then need to provide your own authorization credentials. The connection then becomes self-managed.
For instance, you can immediately start building an agent using GPT-4o-mini with the Retool-managed OpenAI connection. Once your agent is ready for use, you then update the OpenAI connection and provide your own OpenAI API key.
Some AI models are only available for use as self-managed connections.
Available AI providers and models
Retool supports a number of AI providers and their models for use with AI actions and agents. Agents only support models that allow tool creation. Refer to the following information to learn which models are supported with AI actions or agents.
OpenAI
Retool-managed and self-managed OpenAI models are available for use in AI actions and agents.
| Model | AI actions | Agents |
|---|---|---|
| GPT-4.1-mini | ||
| GPT-4.1 | ||
| GPT-4o-mini | ||
| GPT-4o | ||
| GPT-4 | ||
| GPT 3.5 Turbo | ||
| o3 | ||
| o3-mini | ||
| DALL·E | ||
| o1 | ||
| ChatGPT-4o-latest 1 |
Footnotes
-
Not intended for production use. ↩
Anthropic
Retool-managed and self-managed Anthropic models are available for use in AI actions and agents.
| Model | AI actions | Agents |
|---|---|---|
| Claude 4 Sonnet | ||
| Claude 4 Opus | ||
| Claude 3.7 Sonnet | ||
| Claude 3.5 Haiku | ||
| Claude 3.5 Sonnet | ||
| Claude 3 | ||
| Claude 2.1 | ||
| Claude 2 | ||
| Claude Instant 1.2 |
Google Gemini
Self-managed Google Gemini models are available for use in AI actions and agents.
| Model | AI actions | Agents |
|---|---|---|
| Gemini 2.5 Pro | ||
| Gemini 2.0 Flash | ||
| Gemini 1.5 Pro | ||
| Gemini 1.0 Pro |
Azure OpenAI
Self-managed Azure OpenAI models are available for use in AI actions only.
Rather than a predefined set of models from which you select, you create and deploy an Azure OpenAI service with a specific model. You then provide the endpoint and model name when configuring the API credentials.
Amazon Bedrock
Self-managed Amazon Bedrock models are available for use in AI actions only.
Amazon Bedrock is a managed service that can be configured for different AI models, such as Anthropic or Cohere models. The models available for use with Retool AI depend on the models you configure for Bedrock.
Baseten
Retool-managed and self-managed Baseten models are available for use in AI agents only.
| Model | AI actions | Agents |
|---|---|---|
| DeepSeek-V3 | ||
| Llama 4 Maverick | ||
| Llama 4 Scout |
Custom AI provider
Self-managed custom AI provider models are available for use in AI actions and agents.
You can connect a custom AI provider to Retool that adheres to an OpenAI, Anthropic, Google, or Cohere schema.
Model pricing
- Retool-managed LLMs
- Self-managed LLMs
Retool provides access to OpenAI, Anthropic, and Baseten AI models using either a Retool-managed connection or with your own credentials.
Retool-managed LLM connections provide a limited number of tokens to each organization per day and is rate-limited to 250,000 tokens per hour. If you use Vectors in Retool AI, you can reach this limit very quickly. You can configure AI platforms in Retool AI to use your own API credentials for production use.
Retool uses an hourly rate for billable usage of managed LLM connections. The exact cost varies depending on provider costs.
You can provide your own authorization credentials for each AI provider and the models supported by Retool. Retool also supports the use of custom AI providers, allowing you to make use of many more models.
Retool-managed AI models are provided for testing and development purposes. Once you are ready to use them in a production environment, you must provide your own credentials. This ensures that your AI actions and agents aren't restricted by the Retool-managed connection limits.
To simplify billing, Retool charges a flat-rate hourly fee when using a self-managed LLM connection.
Refer to Agent usage for more information about Billing and usage for Retool Agents.