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What is models.dev?

anomalyco/models.dev — explained in plain English

Analysis updated 2026-06-26

3,774TypeScriptAudience · developerComplexity · 1/5Setup · easy

In one sentence

A community-maintained open-source database of AI models from every major provider, listing their capabilities, pricing, context window sizes, and limits in one place so developers stop hunting through separate docs.

Mindmap

mindmap
  root((models.dev))
    Data tracked
      Pricing per token
      Context window
      Capabilities
      Release date
    Format
      TOML files per model
      Public JSON API
    Use cases
      Model comparison
      App integration
      Provider logos
    Contributing
      Add provider folder
      Submit pull request
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Code map

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filefunction / class

What do people build with it?

USE CASE 1

Look up context window size and per-token pricing for any AI model without visiting multiple provider docs

USE CASE 2

Build an app that lets users compare AI models by price, capability, and context length

USE CASE 3

Fetch all model metadata as a single JSON file to power a model-selection feature in an AI tool

USE CASE 4

Contribute a new AI model's specs by adding a TOML file and opening a pull request

What is it built with?

TypeScriptTOML

How does it compare?

anomalyco/models.devarikchakma/maily.todaltonmenezes/aura-theme
Stars3,7743,7723,777
LanguageTypeScriptTypeScriptTypeScript
Setup difficultyeasymoderateeasy
Complexity1/53/51/5
Audiencedeveloperdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min
Open source, check the repository for the specific license terms.

So what is it?

Models.dev is a community-maintained open-source database that tracks AI models from different providers: what they can do, how much they cost, and what their technical limits are. The goal is to have one place where developers can look up information about any AI model rather than hunting through each provider's individual documentation. The data covers things like whether a model supports file attachments, tool calling, or chain-of-thought reasoning, what its pricing is per million tokens for input and output, how large a context window it has, when it was released, and whether its weights are publicly available. Each model's information is stored as a simple TOML file organized by provider inside the repository. The project exposes all this data through a public API: you can fetch a single JSON file containing information about every tracked model. Provider logos are also available as SVG files through the same API. The data is also used internally by opencode, an AI coding tool. Contributing is the main way the database stays current. Anyone can add a new provider or model by creating the appropriate folder and TOML file, then submitting a pull request. A GitHub Action automatically checks that submissions match the required schema before they can be merged. There is also a mechanism for reusing an existing model's definition when one provider is simply wrapping another provider's model, so data does not have to be duplicated. The project is written in TypeScript and is open source. It is designed to be useful to developers building applications that need to compare or select AI models programmatically.

Copy-paste prompts

Prompt 1
Using the models.dev API, write a script that fetches all available models and filters for ones that support tool calling and have a context window over 100k tokens.
Prompt 2
I'm building an AI chat app. Write code that uses models.dev to display a model picker showing price per million tokens for each option.
Prompt 3
How do I add a new AI provider to models.dev? Show me the required folder structure and TOML file format.
Prompt 4
Using models.dev JSON data, compare input token pricing across all OpenAI and Anthropic models and output a sorted table.

Frequently asked questions

What is models.dev?

A community-maintained open-source database of AI models from every major provider, listing their capabilities, pricing, context window sizes, and limits in one place so developers stop hunting through separate docs.

What language is models.dev written in?

Mainly TypeScript. The stack also includes TypeScript, TOML.

What license does models.dev use?

Open source, check the repository for the specific license terms.

How hard is models.dev to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is models.dev for?

Mainly developer.

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