The official model registry for LLMRing - providing up-to-date pricing, capabilities, and metadata for all major LLM providers.
Schema Version 3.5 - Dictionary-based models with standardized fields (e.g., max_input_tokens, dollars_per_million_tokens_input) and per-provider version numbers.
// JavaScript
fetch('https://llmring.github.io/registry/manifest.json')
.then(res => res.json())
.then(data => console.log(data));
// Python
import requests
manifest = requests.get('https://llmring.github.io/registry/manifest.json').json()
print(manifest)
// Fetch OpenAI models (v3.5 format)
fetch('https://llmring.github.io/registry/openai/models.json')
.then(res => res.json())
.then(data => {
console.log(`Found ${Object.keys(data.models).length} OpenAI models`);
console.log('GPT-4o pricing:', data.models['openai:gpt-4o']);
});
# 0) (Optional) Gather sources
uv run registry sources
uv run registry fetch-html --provider openai --output-dir html_cache
uv run playwright install chromium
uv run registry fetch --provider openai --output-dir pdfs
# 1) Generate a draft (best-effort) from PDFs (writes to drafts/)
uv run registry extract --provider openai --pdfs-dir pdfs
# 2) Review differences vs current curated file
uv run registry review-draft --provider openai --draft drafts/openai.2025-08-20.json
# Examine the .diff.json report next to the draft
# 3) Optionally accept all and generate a reviewed file
uv run registry review-draft --provider openai --draft drafts/openai.2025-08-20.json --accept-all
# 4) Promote the reviewed file to publish & archive
uv run registry promote --provider openai --reviewed drafts/openai.reviewed.json
For more information about the LLMRing project:
The registry is automatically updated daily at 6 AM UTC via GitHub Actions. Each update fetches the latest pricing and model information directly from provider documentation.
Each model entry includes:
provider
- Provider identifier (openai, anthropic, google)model_name
- Model identifierdisplay_name
- Human-readable namemax_input_tokens
- Maximum input tokensmax_output_tokens
- Maximum output tokensdollars_per_million_tokens_input
- Cost per million input tokens (USD)dollars_per_million_tokens_output
- Cost per million output tokens (USD)supports_vision
, supports_function_calling
, supports_json_mode
, supports_parallel_tool_calls
is_active
- Whether the model is currently activeBuilt with ❤️ by the LLMRing team | Report an Issue | Last updated: checking...