🤖 AI Models Catalog

The most comprehensive structured catalog of AI models on GitHub

95 providers · 4,587 model files · 2,712 unique model IDs · First-party data only

⭐ If this catalog helps you choose the right model, please star this repo — it helps others discover it!

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Machine-readable YAML catalog of every major AI model provider and their models — pricing, context windows, modalities, capabilities, and more. All data sourced from first-party APIs and official documentation, never third-party aggregators.

Quick start → · Choose a model → · Compare pricing → · 🔍 Search → · Download CSV → · JSON →

🆓 81 free models with tool calling, reasoning, and vision — see the list → · 💰 Cheapest models from $0.01/M tokens — compare pricing → · 🤖 1,080 agentic models for AI agents — find yours →

💡 Try it now — fetch model data and see instant insights:

curl -sL https://github.com/i-need-token/ai-models/releases/latest/download/models.json | python3 -c "
import json,sys; d=json.load(sys.stdin); m=d['models']; p=set(x.get('provider','') for x in m)
A={'openrouter','requesty','auriko','llmgateway','cortecs','aihubmix','orcarouter','fastrouter','302ai','martian','nanogpt','jiekou','venice','meganova'}
f=[x for x in m if x.get('provider') not in A]
tc=sorted([x for x in f if x.get('tool_call') and isinstance(x.get('pricing',{}).get('input'),(int,float)) and x['pricing']['input']>0],key=lambda x:x['pricing']['input'])
cx=sorted([x for x in f if isinstance(x.get('limit',{}).get('context'),(int,float)) and x['limit']['context']>0],key=lambda x:-x['limit']['context'])
fr=[x for x in m if isinstance(x.get('pricing',{}),dict) and x['pricing'].get('unit')=='free']
print(f'📊 {len(m)} models across {len(p)} providers')
print(f'💰 Cheapest tool-calling: {tc[0]["id"]} at ${tc[0]["pricing"]["input"]}/${tc[0]["pricing"]["output"]}/M tokens')
print(f'📏 Largest context: {cx[0]["id"]} — {cx[0]["limit"]["context"]:,} tokens')
print(f'🆓 {len(fr)} free models ({len([x for x in fr if x.get("reasoning")])} with reasoning)')
"

Expected output

📊 4,587 models across 87 providers
💰 Cheapest tool-calling: ling-2.6-flash at $0.01/$0.03/M tokens
📏 Largest context: meta-llama-4-scout — 10,000,000 tokens
🆓 81 free models (33 with reasoning)

💡 Quick Value Demo

What's the cheapest model with tool calling? → ling-2.6-flash at $0.01/$0.03 per M tokens (see all 2,350 →) What's the best free reasoning model? → DeepSeek R1 — 92% MATH-500 (see all 81 free →) Which model has the largest context window? → Gemini 2.5 Pro — 1,048,576 tokens (see all context windows →)

🖥️ Interactive Catalog

🎬 Watch demo (filter, sort, dark mode, calculator)

Try it live → — Search, filter, compare 4,587+ models with 25+ features including dark/light theme, keyboard shortcuts, price calculator, and model picker wizard.

📊 AI Models Landscape — providers, capabilities, pricing, context windows at a glance

Why This Catalog?

🔍 Compare models at a glance	Pricing, context windows, capabilities — all in one place, all structured
📊 4,587 models across 95 providers	From OpenAI to Zhipu, from cloud APIs to open-weights
✅ First-party data only	Every data point comes from the provider's own API or docs
🤖 Machine-readable YAML	TypeScript types + Zod validation = programmatic access with confidence
🔄 Automated sync	Scrape scripts pull fresh data from provider APIs

Contents

• Quick Compare
• 🏆 Model Picks
• Use Cases
• Quick Numbers
• Example Model
• Programmatic Usage
• GitHub Action
• Documentation
• Provider Showcase
• Contributing
• Who's Using This
• License

Quick Compare

Popular models at a glance — full data for 4,587 models

Model	Provider	Context	Input $/M	Output $/M	Tools	Reason	Vision
gpt-4.1	openai	1M	$2	$8	✓		✓
gpt-4.1-mini	openai	1M	$0.40	$1.60	✓		✓
gpt-4.1-nano	openai	1M	$0.10	$0.40	✓		✓
o3	openai	200K	$10	$40	✓	✓	✓
o4-mini	openai	200K	$1.10	$4.40	✓	✓	✓
claude-opus-4	anthropic	200K	$15	$75	✓	✓	✓
claude-sonnet-4	anthropic	200K	$3	$15	✓	✓	✓
claude-haiku-4	anthropic	200K	$1	$5	✓	✓	✓
gemini-2.5-pro	google	1M	$1.25	$10	✓	✓	✓
gemini-2.5-flash	google	1M	$0.15	$0.60	✓	✓	✓
deepseek-r1	deepseek	128K	$0.55	$2.19		✓
deepseek-chat	deepseek	128K	$0.14	$0.28	✓
llama-4-maverick	meta	1M	$0.20	$0.20	✓		✓
llama-4-scout	meta	10M	$0.03	$0.03	✓		✓
grok-3	xai	131K	$3	$15	✓		✓
grok-3-mini	xai	131K	$0.30	$0.50	✓	✓	✓
mistral-large	mistral	128K	$2	$6	✓		✓
qwen3-235b-a22b	alibaba	128K	$0.14	$0.42	✓	✓	✓
qwen3-30b-a3b	alibaba	128K	$0.03	$0.05	✓	✓	✓

📖 How to read this table

• Context: Maximum context window (input + output tokens)
• Input/Output $/M: Price per million tokens
• Tools: Supports function/tool calling
• Reason: Uses chain-of-thought reasoning
• Vision: Accepts image input
• Prices shown are for standard (non-cached) API calls. Many providers offer 50-90% discounts for cached inputs.

🏆 Model Picks

Curated recommendations for common use cases — from 4,587 models across 95 providers

Use Case	Model	Why	Input $/M	Context
Coding	gpt-4.1	Best code generation + 1M context	$2	1M
Coding (cheap)	gpt-4.1-nano	20x cheaper, great for autocomplete	$0.10	1M
Reasoning	o4-mini	Best cost-effective reasoning	$1.10	200K
Reasoning (power)	claude-opus-4	Deepest reasoning for hard problems	$15	200K
Agents	claude-sonnet-4	Best tool use + reasoning balance	$3	200K
Agents (cheap)	gemini-2.5-flash	Fastest agent loop under $1	$0.15	1M
Vision	gemini-2.5-pro	Best multimodal understanding	$1.25	1M
Free	llama-4-scout	10M context, open weights, free on Groq	$0	10M
Open weights	deepseek-r1	Best open reasoning model	$0.55	128K
Large context	gemini-2.5-flash	1M context at lowest price	$0.15	1M

Use Cases

Use Case	How This Catalog Helps
💰 Find the cheapest model	Pricing comparison across 95 providers
🔎 Pick the right model	Model comparison by capability, context, cost
🔍 Search & compare models	Interactive catalog — search, filter, compare, price calc, model picker, copy-as-code, share, j/k nav
🔌 Build an API gateway	Structured pricing + modality data for routing decisions
📊 Track the AI landscape	2,712 models with release dates, deprecation status
🤖 Power an AI tool	TypeScript types + Zod validation = type-safe access
🌍 Find local/EU providers	Provider overview with market segmentation
🎯 Choose the right model	Model selection guide — decision framework
💸 Optimize API costs	Cached pricing — 1,374 models with 50-90% savings
🧪 Prototype for free	Free models — 81 models at zero cost
💬 Build chat apps	Chat models — 2,350 models with tool calling
🖼️ Process images/audio	Multimodal models — 1,519 models with vision/audio/video
🔎 Power semantic search	Embedding models — vector search & RAG
🤖 Build AI agents	Agentic models — 1,080 models with tool_call + reasoning
💻 Generate & review code	Code models — 189 code-focused models
🎙️ Add voice/speech	Audio models — 118 audio input + 34 audio output
🔄 Switch from OpenAI	OpenAI alternatives — pricing, free options, compat

Quick Numbers

Metric	Count
Providers	95
Model files	4,587
Unique model IDs	2,712
Model families	441
Reasoning models	1,306
Tool-calling models	2,350
Open-weight models	527
Free models	81
Vision (image input) models	1,487
Image output models	28
Audio input models	118
Audio output models	34
Video input models	167

Data at a Glance

Each model is a single YAML file with structured metadata:

id: gpt-4.1
name: GPT-4.1
family: gpt-4.1
tool_call: true
structured_output: true
pricing:
  input: 2.0 # USD per million tokens
  output: 8.0
  cache_read: 0.5
limit:
  context: 1047576 # tokens (~1M)
  output: 32768
modalities:
  input: [text, image]
  output: [text]
release_date: "2026-05-18"
last_updated: "2026-05-18"

Same model as JSON (from models.json)

{
  "id": "gpt-4.1",
  "name": "GPT-4.1",
  "family": "gpt-4.1",
  "tool_call": true,
  "structured_output": true,
  "pricing": { "input": 2.0, "output": 8.0, "cache_read": 0.5 },
  "limit": { "context": 1047576, "output": 32768 },
  "modalities": { "input": ["text", "image"], "output": ["text"] },
  "release_date": "2026-05-18",
  "last_updated": "2026-05-18"
}

Pricing Types

Type	When	Example
TokenPricing	Per-million-token pricing	input: 2.5, output: 10
VideoPricing	Per-second pricing	unit: per_second, price: 0.03
UnitPricing	Per-image or per-request	unit: per_image, price: 0.04
FreePricing	No cost	unit: free

Covered Providers

Model Producers (develop their own models)

• Anthropic — Claude series
• Google — Gemini series
• Meta — Llama series
• OpenAI — GPT series
• DeepSeek — DeepSeek-V/R series
• Alibaba Cloud — Qwen series
• Mistral AI — Mistral series
• Cohere — Command series
• xAI — Grok series
• Reka AI — Reka series
• AI21 Labs — Jamba series
• 01.AI — Yi series
• ByteDance — Doubao series
• MiniMax — MiniMax series
• Moonshot AI — Kimi series
• Zhipu AI — GLM series
• NVIDIA — Nemotron series
• IBM — Granite series
• Microsoft — Phi series
• StepFun — Step series
• iFlytek — SparkDesk series
• Baidu — ERNIE series
• Baichuan AI — Baichuan series
• Tencent — Hunyuan series
• Xiaomi — MiMo series
• Sarvam AI — Sarvam series
• InclusionAI — Book series
• Writer — Palmyra series
• Upstage — Solar series
• Voyage AI — Voyage series

Inference Platforms (host and serve models)

• Amazon Bedrock — Multi-provider inference on AWS
• Azure OpenAI Service — OpenAI models on Azure
• Google Vertex AI — Multi-provider inference on GCP
• OpenRouter — 300+ models with unified API
• Together AI — Open-source model hosting
• Fireworks AI — Fast inference for open models
• Groq — LPU-accelerated inference
• Cerebras — CS-3 wafer-scale inference
• DeepInfra — Cost-effective model hosting
• SiliconFlow — GPU cloud inference
• Novita AI — Multi-model API
• SambaNova — SN40L accelerated inference
• Cohere — Command models + hosted models
• Databricks — MosaicML inference
• Cloudflare Workers AI — Edge inference
• DigitalOcean — GPU Droplets inference
• Nebius — AI cloud inference
• OVHcloud — AI Endpoints
• Scaleway — GPU inference
• Vultr — Cloud inference
• Chutes — Community inference
• Kluster AI — Distributed inference
• NanoGPT — Simple API, 500+ models
• And 40+ more platforms…

Full Provider List (95)

01.AI · 302.AI · AI21 Labs · AIHubMix · AI/ML API · Aion Labs · Alibaba Cloud · Amazon Bedrock · Amazon Nova · Anthropic · Arcee AI · Auriko · Azure OpenAI · Baichuan AI · Baidu · Baseten · Berget · ByteDance · Cerebras · Chutes · Clarifai · CloudFerro Sherlock · Cloudflare Workers AI · Cohere · Cortecs · DInference · Databricks · DeepInfra · DeepSeek · DigitalOcean · evroc · FastRouter · Fireworks AI · FriendliAI · GMI Cloud · Google · Google Vertex AI · Groq · HPC-AI Cloud · Hyperbolic · IBM Granite · iFlytek SparkDesk · Inception Labs · InclusionAI · Inference.net · Kluster AI · LLM Gateway · Martian · MegaNova · Meta Llama · Microsoft Phi · MiniMax · Mistral AI · Mixlayer · MoArk AI · Moonshot AI · Morph · NanoGPT · Nebius · NeuralWatt · Nous Research · Novita AI · NVIDIA · OpenAI · OpenRouter · OrcaRouter · OVHcloud · PPIO · Perplexity · Privatemode AI · Qiniu AI · Regolo · Reka AI · Requesty · SambaNova · Sarvam AI · Scaleway · SiliconFlow · SiliconFlow CN · StepFun · SubModel · Tencent Cloud TokenHub · Tencent Hunyuan · TextSynth · Together AI · Upstage · Venice AI · Voyage AI · Vultr · Wafer · Writer · xAI Grok · Xiaomi · Zhipu AI · 接口 AI

Quick Start

Browse the Data

No installation needed — just browse providers/<provider>/models/ for YAML files. Every file is human-readable.

Install from npm

npm install ai-models

import catalog from "ai-models"; // 4,587 models as JSON
import type { Model } from "ai-models"; // TypeScript types

Install & Sync

# Install dependencies
npm install

# Fetch latest data from a specific provider
npx tsx scripts/sync.ts openai
npx tsx scripts/sync.ts anthropic

# Fetch all providers
npx tsx scripts/sync.ts

# Validate all YAML files
npx tsx scripts/validate.ts

# Compute catalog statistics
npx tsx scripts/stats.ts

# Compile to a single models.json
npx tsx scripts/compile.ts

Or use the Makefile shortcuts:

make install    # npm install
make validate   # validate all YAML
make scrape     # sync all providers
make build      # compile models.json
make stats      # compute statistics
make check      # run all checks (fmt + lint + typecheck + validate)

Use Programmatically

import { ModelSchema } from "./types/schemas";
import { parse } from "yaml";
import { readFileSync } from "fs";

// Load and validate a model
const raw = readFileSync("providers/openai/models/gpt-4.1.yaml", "utf-8");
const model = ModelSchema.parse(parse(raw));

console.log(model.pricing); // { input: 2, output: 8, cache_read: 0.5 }
console.log(model.limit); // { context: 1047576, output: 32768 }
console.log(model.modalities); // { input: ["text", "image"], output: ["text"] }

Download Data

Available in JSON and CSV formats from GitHub Releases:

# JSON — full metadata (2.3 MB)
curl -sLO https://github.com/i-need-token/ai-models/releases/latest/download/models.json

# CSV — flat table for Excel/Google Sheets (560 KB)
curl -LO https://github.com/i-need-token/ai-models/releases/latest/download/models.csv

<!-- Use in any HTML page -->
<script type="module">
  const catalog = await fetch(
    "https://github.com/i-need-token/ai-models/releases/latest/download/models.json",
  ).then((r) => r.json());
  console.log(catalog.models.length); // 4,587
</script>

# Python — no pip install needed
import urllib.request, json
catalog = json.loads(urllib.request.urlopen("https://github.com/i-need-token/ai-models/releases/latest/download/models.json").read())
print(len(catalog['models']))  # 4587

# Quick stats with jq
curl -sL https://github.com/i-need-token/ai-models/releases/latest/download/models.json | jq '.models | length'

See API & Programmatic Access for full usage examples in JavaScript and Python.

Use as GitHub Action

- uses: i-need-token/ai-models@v0.2.2
  id: catalog

- name: Use catalog data
  run: |
    echo "Models: ${{ steps.catalog.outputs.model-count }}"
    echo "Providers: ${{ steps.catalog.outputs.provider-count }}"
    echo "File: ${{ steps.catalog.outputs.file-path }}"

Download a specific version or format:

- uses: i-need-token/ai-models@v0.2.2
  with:
    version: v0.1.0 # specific release tag
    format: csv # csv or json
    output-dir: data # directory to save files

See action.yml for all inputs and outputs.

🎬 Live demo output (from our CI)

📊 4587 models from 87 providers
📁 Data saved to model-data/models.json

💰 Cheapest tool-calling models:
  bdc-coder: $0.01/$0.01/M tokens
  ling-2.6-flash: $0.01/$0.03/M tokens
  klusterai--Meta-Llama-3.1-8B-Instruct-Turbo: $0.015/$0.02/M tokens
  granite-4.0-h-micro: $0.017/$0.112/M tokens

🆓 Free reasoning models:
  gemma-4-26b-a4b-it: 262K context
  gemma-4-31b-it: 262K context

View the live workflow →

Project Structure

├── providers/           # 95 provider directories
│   └── <provider>/
│       ├── provider.yaml    # Provider metadata (name, URL, API endpoints)
│       ├── scrape.ts        # Data acquisition script
│       ├── models/          # YAML model data files
│       └── README.md        # Provider-specific notes
├── types/               # TypeScript type definitions + Zod schemas
│   ├── model.ts             # Model, Snapshot, ModelModality
│   ├── pricing.ts           # TokenPricing, VideoPricing, UnitPricing, FreePricing
│   ├── provider.ts          # Provider, ProviderGroup
│   └── schemas.ts           # Zod runtime validation
├── scripts/             # CLI tools
│   ├── sync.ts              # Orchestration: scrape → write YAML
│   ├── validate.ts          # Validate all YAML against schemas
│   ├── stats.ts             # Compute catalog statistics
│   ├── compile.ts           # Compile to dist/models.json
│   └── lib/                 # Shared utilities
└── docs/                # Documentation (English + 中文)

Adding a New Provider

1. Create providers/<id>/scrape.ts with a scrape() function that returns { provider, models }
2. Data must come from a first-party source (provider's API or website)
3. Include a discovery step — no hardcoded model ID lists
4. Run npx tsx scripts/sync.ts <id> to generate initial data
5. Validate with npx tsx scripts/validate.ts

See docs/data-acquisition.md for detailed guidelines.

Documentation

Document	Description
Tool Calling Models	2,350 tool-calling models — cheapest, largest context, free
Vision Models	1,487 vision models — cheapest, largest context, open-weight
Image Generation	28 image generation models — DALL·E, Imagen, GPT-5 Image
Audio Models	118 audio input + 34 audio output models
Code Models	189 code-focused models across 41 providers
Agentic Models	1,080 models with tool calling + reasoning for AI agents
Chat Models	2,350 models with tool calling for chat applications
Multimodal Models	1,519 models with image/audio/video input
Embedding Models	5 embedding models for search, RAG, similarity
Video Models	167 video input + 4 video output models
Structured Output	829 JSON-mode models — cheapest, free, with tool calling
🔍 Interactive Catalog	Search, sort, and filter all 4,587 models in your browser
Quick Start Guide	Find the right model in 30 seconds
Model Selection Guide	Decision framework: free, best value, large context models
Model Selection Cheatsheet	Quick-reference: best model by budget and use case
AI Model Picker	4-question wizard: find the best model for your use case
Benchmarks & Leaderboards	MMLU, MATH, HumanEval, SWE-bench, Chatbot Arena guide
Migration Guide	Switch providers — pricing, API compatibility, checklist
API & Programmatic Access	Download models.json, code examples in JS/Python
Code Examples	Practical examples in TypeScript, Python, Go, Rust, jq
FAQ	Common questions about the catalog, data, and contributing
Glossary	Key terms and definitions for AI model terminology
Model Comparison	Compare flagship, cost-effective, free, and open-weight models
Pricing Comparison	Side-by-side pricing across providers and platforms
Cached Pricing	1,374 models with prompt caching — 50-90% input cost savings
Modality Matrix	Vision, image gen, audio, video — which models support what
Context Window Comparison	Largest context windows, best value per tier
Large Context Models	2,195 models with 128K+ context — 397 with 1M+
Small & Edge Models	1,153 models under 10B params for on-device use
Provider Comparison	Top 30 providers by model count, capabilities, pricing
Free AI Models	81 free models — tool calling, reasoning, vision at no cost
Open-Weight Models	513 open-weight models — run on your own infrastructure
Reasoning Models	1,306 reasoning models — chain-of-thought and extended thinking
OpenAI Alternatives	GPT-4/GPT-3.5 alternatives — pricing, free options, compat
Provider Overview	All 95 providers organized by type and market
Data Schema Reference	Complete YAML schema — model, pricing, snapshot, provider
Data Acquisition	How we acquire and update model data
Design Principles & Pitfalls	Lessons learned from building the catalog

中文文档：

文档	描述
工具调用模型	2,350 个工具调用模型 — 最便宜、最大上下文、免费
视觉模型	1,487 个视觉模型 — 最便宜、最大上下文、开源权重
快速入门	30 秒内找到适合的模型
图像生成	28 个图像生成模型 — DALL·E、Imagen、GPT-5 Image
音频模型	118 个音频输入 + 34 个音频输出模型
视频模型	167 个视频输入 + 4 个视频输出模型
API 与编程访问	下载 models.json，JS/Python 代码示例
代码示例	TypeScript、Python、Go、Rust、jq 实用示例
常见问题	关于目录、数据和贡献的常见问题
结构化输出	829 个 JSON 模式模型 — 最便宜、免费、带工具调用
模型对比	旗舰、高性价比、免费和开源模型对比
定价对比	各提供商和平台定价并排对比
缓存定价	1,374 个支持提示缓存的模型 — 输入成本节省 50-90%
模态矩阵	视觉、图像生成、音频、视频 — 各模型支持什么
上下文窗口对比	最大上下文窗口，各层级最佳性价比
大上下文模型	2,195 个 128K+ 上下文模型 — 397 个 1M+
小型/边缘模型	1,153 个 10B 参数以下模型，适合端侧部署
提供商对比	按模型数量、能力、定价对比前 30 个提供商
免费 AI 模型	81 个免费模型 — 工具调用、推理、视觉零成本
开源权重模型	513 个开源权重模型 — 自有基础设施运行
提供商概览	95 个提供商按类型和市场分类
推理模型	1,306 个推理模型 — 链式思维和扩展思考
数据 Schema 参考	完整 YAML Schema — 模型、定价、快照、提供商
数据采集	数据采集指南
设计原则与陷阱	经验教训
智能体模型	1,080 个工具调用+推理模型，用于 AI 智能体
代码模型	189 个代码模型：生成、审查、调试
OpenAI 替代方案	GPT-4/GPT-3.5 替代方案：定价、免费选项、兼容性
聊天模型	2,350 个带工具调用的聊天模型
多模态模型	1,519 个支持图像/音频/视频输入的模型
嵌入模型	5 个嵌入模型用于搜索、RAG、相似度
模型选择指南	决策框架：免费、最佳性价比、大上下文模型
模型选择速查表	按预算和使用场景快速选择模型
迁移指南	切换提供商：定价、API 兼容性、检查清单
术语表	AI 模型术语的关键词和定义

Design Principles

• First-party data only — all model data comes from the provider's own API or website
• Dynamic discovery — scrape functions discover models from the source, not from hardcoded lists
• Include deprecated, exclude retired — deprecated models are included with deprecated: true; retired (inaccessible) models are excluded
• Never fabricate data — if required data is missing, skip the model with a warning rather than filling in guessed values
• YAML source format — human-readable, supports comments, machine-parseable
• Snapshot inheritance — dated model versions are nested within the parent model, inheriting all fields

Contributing

Contributions are welcome! Whether it's adding a new provider, fixing data, or improving documentation:

1. Fork the repository
2. Create your feature branch (git checkout -b feature/my-provider)
3. Follow the data acquisition guidelines
4. Validate your changes (npx tsx scripts/validate.ts)
5. Submit a pull request

Please read CONTRIBUTING.md for detailed guidelines.

Alternatives

Project	Scope	Data Source	Format	Auto-Update	Free
This catalog	95 providers, 4,587+ models	First-party APIs	YAML + JSON + CSV	Weekly CI	✅
Artificial Analysis	~30 providers	Mixed	Web UI	✅	Partial
LLM Price	~25 providers	Mixed	Web UI	✅	✅
OpenRouter models	OpenRouter only	OpenRouter API	Web UI	✅	✅
Helicone models	~20 providers	Mixed	Web UI	✅	Partial
BerriAI/litellm	100+ providers	Community	Python config	✅	✅
dariubs/awesome-ai-models	~20 providers	Manual	Markdown list	❌	✅
Vellum AI	~15 providers	Mixed	Web UI + API	✅	Partial
openai/models	OpenAI only	OpenAI API	Python SDK	✅	✅

Key differentiators of this catalog:

• First-party data only — scraped directly from provider APIs, not aggregated from third parties
• Machine-readable YAML — structured data with Zod validation, not just a web UI
• Multiple access formats — npm, CDN, CSV, GitHub Action, Hugging Face dataset
• Comprehensive metadata — pricing, context windows, modalities, capabilities, snapshots
• Bilingual docs — 34 English + 34 Chinese documentation pages
• Open data — all model data is open and programmatically accessible

Ecosystem & Integrations

Integration	Description	Link
npm package	Install models.json via npm	npm install ai-models
jsDelivr CDN	Fetch models.json from CDN	cdn.jsdelivr.net/npm/ai-models
GitHub Action	Use in CI/CD workflows	action.yml
Hugging Face	Dataset on HF Hub	huggingface.co/datasets/i-need-token/ai-models
CSV download	Import into Excel/Sheets	GitHub Releases
Interactive catalog	Search, filter, compare, price calculator, model picker	i-need-token.github.io/ai-models
SEO comparison pages	21 curated comparison pages for discoverability	Best Models, Free Models, Pricing, OpenAI Alt, By Provider, Context, Coding, Agents, Reasoning, Cheapest, Tool Calling, Pricing Calc, Image Gen, Vision, Structured Output, Open Source, Multimodal, State of AI, Benchmarks, ChatGPT vs Claude vs Gemini, Comparison Chart

What's New

v0.2.0 (May 2025)

• 21 SEO comparison pages — Best Models, Free Models, LLM Pricing, OpenAI Alternatives, By Provider, Context Windows, Coding, Agents, Reasoning, Cheapest, Tool Calling, Pricing Calculator, Image Generation, Open Source, Multimodal, State of AI Models 2025
• Interactive catalog — 25+ features including dark/light theme, keyboard shortcuts, model detail modal, price calculator, model picker wizard, copy as code, share button, j/k vim navigation
• 95 providers — comprehensive coverage of all major AI providers
• 4,587+ models — with pricing, context windows, modalities, and capabilities
• GitHub Action v2 — version, format, and output-dir inputs
• npm package — npm install ai-models
• 70 docs — 35 EN + 35 ZH, all bilingual, all cross-linked

Roadmap

• Embedding models documentation → docs/embedding-models.md
• Provider comparison → docs/provider-comparison.md
• Large context models → docs/large-context-models.md
• Small/edge models → docs/small-models.md
• Migration guide → docs/migration-guide.md
• Model benchmarking data integration
• Streaming support metadata
• Fine-tuning availability tracking
• Regional availability data
• Community-contributed model reviews
• 🔜 REST API — hosted API for querying the catalog
• 🔜 Historical pricing — track pricing changes over time
• 🔜 Community scrapers — enable community-contributed scrape scripts with automated validation

Who's Using This?

Built something with this catalog? Open a PR to add your project!

Use Case	How the Catalog Is Used
AI API gateways	Route requests to the cheapest provider with real-time pricing data
Model comparison tools	Compare capabilities, context windows, and costs across providers
Cost optimization	Find the cheapest model for each task (reasoning, vision, tool calling)
AI agent frameworks	Select models with tool calling + structured output for agent workflows
Research & analysis	Track the AI landscape — 2,712 models with release dates and deprecation
CI/CD pipelines	Use the GitHub Action to fetch model data in workflows
Data dashboards	Import CSV into Excel/Google Sheets for visual pricing analysis
Chatbot builders	Pick the right model by context window, modality, and budget

Contributors

Thanks to everyone who has contributed to this catalog!

Want to contribute? Check out CONTRIBUTING.md for guidelines.

• 📋 Changelog — what's new in each release
• 🔒 Security Policy — reporting vulnerabilities

Project Timeline

Date	Milestone
2026-05	🚀 Public launch — 4,587 models, 95 providers, 68 docs
2026-05	📊 Interactive catalog live at GitHub Pages
2026-05	📦 npm package, CSV export, GitHub Action
2026-05	🌐 Bilingual docs — 34 EN + 34 ZH pages
2026-05	🤖 1,080 agentic models, 2,350 tool-calling models
Future	📈 More providers, REST API, historical pricing, benchmarks

Sponsors

Support this project by sponsoring us on GitHub. Your sponsorship helps maintain and expand the catalog.

License

MIT