Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Provides daily-updated, authoritative rankings and metadata of state-of-the-art AI models aggregated from leading sources via JSON, API, or local queries.
Provides daily-updated, authoritative rankings and metadata of state-of-the-art AI models aggregated from leading sources via JSON, API, or local queries.
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The definitive open-source database of State-of-the-Art AI models. Auto-updated daily from LMArena, Artificial Analysis, and HuggingFace.
AI models are released weekly. Keeping track is impossible. This project: Curates authoritative data - LMArena Elo rankings, manual curation for video/image/audio models Updates daily via GitHub Actions Exports to JSON/CSV/SQLite - Use in your own projects Provides multiple interfaces - Static files, REST API, or MCP server
# Latest data (updated daily) curl -O https://raw.githubusercontent.com/romancircus/sota-tracker-mcp/main/data/sota_export.json curl -O https://raw.githubusercontent.com/romancircus/sota-tracker-mcp/main/data/sota_export.csv
git clone https://github.com/romancircus/sota-tracker-mcp.git cd sota-tracker-mcp # Query with sqlite3 sqlite3 data/sota.db "SELECT name, sota_rank FROM models WHERE category='llm_api' ORDER BY sota_rank LIMIT 10" # List forbidden/outdated models sqlite3 data/sota.db "SELECT name, reason, replacement FROM forbidden"
The recommended approach for Claude Code users is static file embedding (lower token cost than MCP): # Set up daily auto-update of CLAUDE.md cp scripts/update_sota_claude_md.py ~/scripts/ # Enable systemd timer (runs at 6 AM daily) systemctl --user enable --now sota-update.timer # Or run manually python ~/scripts/update_sota_claude_md.py --update This embeds a compact SOTA summary directly in your ~/.claude/CLAUDE.md file.
# Start the API server uvicorn rest_api:app --host 0.0.0.0 --port 8000 # Query endpoints curl "http://localhost:8000/api/v1/models?category=llm_api" curl "http://localhost:8000/api/v1/forbidden" curl "http://localhost:8000/api/v1/models/FLUX.1-dev/freshness"
MCP support is available but disabled by default (higher token cost). To enable: # Edit .mcp.json to add the server config cat > .mcp.json << 'EOF' { "mcpServers": { "sota-tracker": { "command": "python", "args": ["server.py"] } } } EOF
SourceDataUpdate FrequencyLMArenaLLM Elo rankings (6M+ human votes)DailyArtificial AnalysisLLM benchmarks, pricing, speedDailyHuggingFaceModel downloads, trendingDailyManual curationVideo, Image, Audio, Video2Audio modelsAs needed
CategoryDescriptionTop Models (Feb 2026)llm_apiCloud LLM APIsGemini 3 Pro, Grok 4.1, Claude Opus 4.5llm_localLocal LLMs (GGUF)Qwen3, Llama 3.3, DeepSeek-V3llm_codingCode-focused LLMsQwen3-Coder, DeepSeek-V3image_genImage generationZ-Image-Turbo, FLUX.2-dev, Qwen-ImagevideoVideo generationLTX-2, Wan 2.2, HunyuanVideo 1.5video2audioVideo-to-audio (foley)MMAudio V2 LargettsText-to-speechChatterboxTTS, F5-TTSsttSpeech-to-textWhisper Large v3embeddingsVector embeddingsBGE-M3
EndpointDescriptionGET /api/v1/models?category=XGet SOTA for a categoryGET /api/v1/models/:name/freshnessCheck if model is current or outdatedGET /api/v1/forbiddenList outdated models to avoidGET /api/v1/compare?model_a=X&model_b=YCompare two modelsGET /api/v1/recent?days=30Models released in past N daysGET /api/v1/recommend?task=chatGet recommendation for a taskGET /healthHealth check
# Install dependencies pip install -r requirements.txt pip install playwright playwright install chromium # Run all scrapers python scrapers/run_all.py --export # Output: # data/sota_export.json # data/sota_export.csv # data/lmarena_latest.json
This repo uses GitHub Actions to: Daily: Scrape all sources, update database, commit changes Weekly: Create a tagged release with JSON/CSV exports To enable on your fork: Fork this repo Go to Settings โ Actions โ Enable workflows Data will auto-update daily at 6 AM UTC
sota-tracker-mcp/ โโโ server.py # MCP server (optional) โโโ rest_api.py # REST API server โโโ init_db.py # Database initialization + seeding โโโ requirements.txt # Dependencies โโโ data/ โ โโโ sota.db # SQLite database โ โโโ sota_export.json # Full JSON export โ โโโ sota_export.csv # CSV export โ โโโ forbidden.json # Outdated models list โโโ scrapers/ โ โโโ lmarena.py # LMArena scraper (Playwright) โ โโโ artificial_analysis.py # AA scraper (Playwright) โ โโโ run_all.py # Unified runner โโโ fetchers/ โ โโโ huggingface.py # HuggingFace API โ โโโ cache_manager.py # Smart caching โโโ .github/workflows/ โโโ daily-scrape.yml # GitHub Actions workflow
Found a model that's missing or incorrectly ranked? For manual additions: Edit init_db.py and submit a PR For scraper improvements: Edit files in scrapers/ For new data sources: Add a new scraper and update run_all.py See CONTRIBUTING.md for full developer setup and PR process.
The repo now supports updating agents.md files for OpenCode agents: # Update your agents.md with latest SOTA data python update_agents_md.py # Minimal version (top 1 model per category, lightweight) python update_agents_md.py --minimal # Custom categories and limit python update_agents_md.py --categories llm_local image_gen --limit 3 # Force refresh from sources first python update_agents_md.py --refresh
Add to your cron or systemd timer for daily updates: # ~: crontab -e @daily python ~/Apps/sota-tracker-mcp/update_agents_md.py Or systemd: # ~/.config/systemd/user/sota-update.service [Unit] Description=Update SOTA models for agents After=network.target [Service] ExecStart=%h/Apps/sota-tracker-mcp/update_agents_md.py [Install] WantedBy=default.target # ~/.config/systemd/user/sota-update.timer [Unit] Description=Daily SOTA data update OnCalendar=daily AccuracySec=1h [Install] WantedBy=timers.target # Enable systemctl --user enable --now sota-update.timer See CONTRIBUTING.md for full setup guide
This project aggregates publicly available benchmark data from third-party sources. We do not claim ownership of rankings, Elo scores, or benchmark results.
SourceDataPermissionLMArenaChatbot Arena Elo rankingsrobots.txt: Allow: /Artificial AnalysisLLM quality benchmarksrobots.txt: Allow: / (explicitly allows AI crawlers)HuggingFaceModel metadata, downloadsPublic APIOpen LLM LeaderboardOpen-source LLM benchmarksCC-BY license
All benchmark scores and rankings are the intellectual work of their respective sources This project provides aggregation and tooling, not original benchmark data Data is scraped once daily to minimize server load If you are a data source and wish to be excluded, please open an issue
This project: Aggregates factual data (not copyrightable) Adds value through tooling (API server, unified format, forbidden list) Attributes all sources with links Does not compete commercially with sources Respects robots.txt permissions
MIT - See LICENSE for details. The code in this repository is MIT licensed. The data belongs to its respective sources (see attribution above).
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Largest current source with strong distribution and engagement signals.