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Open LLM Leaderboard v2 Model Search
x402
Open LLM Leaderboard v2 Model Search is a paid API for AI agents from api.companyrecords-api.workers.dev, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-24).
Searches the archived Hugging Face Open LLM Leaderboard v2 (4,576 models) by name and returns benchmark scores, parameter count, license, and hub metadata sorted by average score.
Price / call$0.002
Success—
StatusUnknown
How this service works
Pay-per-call company registry, government, legal and B2B data tools for AI agents, from official registers and public sources. Payment: x402, USDC on Base, Solana, Arc, Polygon, Arbitrum, Monad, World Chain, Optimism, Avalanche, Celo or Stellar, or RLUSD/XRP on the XRP Ledger. No signup, no API key; a failed call is not charged.
Output
Returns a JSON object with the search query, source URL, total match count, rows scanned, leaderboard freeze date, and an array of matching models sorted by average score descending. Each model entry includes: model name, Hugging Face URL, average score, IFEval, BBH, MATH Lvl 5, GPQA, MUSR, MMLU-PRO scores, parameter count in billions, hub likes, and license string.
Example use cases
Comparing Llama model benchmark scores
“Can you look up all the Llama-3 models on the Open LLM Leaderboard and show me their average score, BBH, and MMLU-PRO results? Give me up to 15 results.”
Finding best open-source model by license
“I need to find the top-scoring Apache-2.0 licensed models on the Open LLM Leaderboard — search for 'apache' and return the top 10 with their average score and parameter count.”
Researching a specific model's full benchmark profile
“What are the IFEval, GPQA, MUSR, and MATH Lvl 5 scores for Qwen2.5-72B on the Hugging Face Open LLM Leaderboard? Show me up to 5 matching models.”
Technical details
Endpoint
GEThttps://api.companyrecords-api.workers.dev/api/b2b/openllm-leaderboard?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need to look up benchmark performance data for one or more open-source LLMs by name from the Hugging Face Open LLM Leaderboard v2. It's ideal for comparing models on IFEval, BBH, MATH Lvl 5, GPQA, MUSR, or MMLU-PRO, or for retrieving metadata like parameter count, license, and community likes. Prefer this over general web search when you need structured, comparable numeric benchmark data across multiple models in a single call.
Side effects
- Query string shorter than 2 or longer than 60 characters returns a validation error
- No models matching the query returns an empty results array
- Limit parameter outside 1–20 range may be rejected or clamped
- Stale data: leaderboard frozen since March 2025, so newer models not present
- Payment failure (x402) if USDC balance is insufficient
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"query": "Yi-1.5",
"source": "https://huggingface.co/datasets/open-llm-leaderboard/contents",
"matches": 18,
"results": [
{
"bbh": 44.26,
"url": "https://huggingface.co/01-ai/Yi-1.5-34B-Chat",
"gpqa": 15.32,
"musr": 13.06,
"model": "01-ai/Yi-1.5-34B-Chat",
"ifeval": 60.67,
"license": "apache-2.0",
"mmluPro": 39.12,
"hubLikes": 268,
"mathLvl5": 27.72,
"averageScore": 33.36,
"parametersBillions": 34.39
},
{
"bbh": 36.95,
"url": "https://huggingface.co/01-ai/Yi-1.5-9B-Chat",
"gpqa": 11.3,
"musr": 12.84,
"model": "01-ai/Yi-1.5-9B-Chat",
"ifeval": 60.46,
"license": "apache-2.0",
"mmluPro": 33.06,
"hubLikes": 141,
"mathLvl5": 22.58,
"averageScore": 29.53,
"parametersBillions": 8.83
}
],
"checkedAt": "2026-10-23T09:37:40.668Z",
"rowsScanned": 4576,
"rowsInDataset": 4576,
"leaderboardFrozenSince": "2025-03-20"
}
}Tags
x402
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