0 to 1000, built from real human preference. No LLM grading another LLM. Three parts:

Every comparison runs the same automated pipeline. Nobody curates it.

• Same prompt, every model. Each model in a challenge receives the exact same input. No special treatment, no warm-up round.
• Automated pipeline. Responses are generated via OpenRouter, Replicate,and direct provider APIs via scripts. No human selection bias.
• Controlled parameters. Pre-generated responses use temperature=0.7 and effectively unlimited output tokens. GPT-5.1 runs at provider default. Every response ships a reproducibility card, so you can call us out.
• No system prompts for pre-generated content. User prompt only. What the model sees is what you see.
• One shot, no cherry-picking. One attempt per model, never re-rolled. What the API coughed up is what ships.

Challenges are the prompts behind every comparison. They exist to find the gaps.

• Capability-specific. Each targets one skill: coding, reasoning, writing, analysis, instruction following, visual output.
• Model-agnostic prompts. No provider-specific keywords, no prompt tricks that advantage one model family.
• High quality ceiling. Open-ended by design. A model ten years from now should still beat today's.

Rankings on the arena come from real votes, weighted. No synthetic benchmarks, and no model grading another.

• Challenge win rates. The primary signal. Each duel win adds to that challenge category's score.
• Category coverage. Models rank inside each category. A stable rank needs participation. No ducking the hard ones.
• Consistency matters. Steady across many beats one standout. A viral moment isn't a career.
• One vote per user per duel. Anonymous and deduplicated. No ballot stuffing.
• Blind voting available. Blind mode hides names until after the vote. People vote differently when they can't see the logo.

Community votes power every ranking, so we are unpleasant about protecting them.

• Deduplication. One vote per model pair per challenge, on a unique DB constraint. The database said no.
• Rate limiting. Signed in: 200 votes/hour. Anonymous: 30, keyed by IP hash. Touch grass between votes.
• Voter fingerprinting. Anonymous votes tie to a hashed IP. Client IDs are hashed too. We trust you. Just not that much.
• Minimum sample size. 10 duels minimum before the leaderboard. Credibility down-weights small counts further.
• Server-side normalization. IDs are validated on insert. Malformed data gets rejected. We've seen what the internet sends.

Models also compete in 15 category arenas, each scoped to one capability. Good at code is not good at everything.

Same Rival Score formula, scoped to that category's challenges. Explore them on the arena

Snapshotted daily, so the board shows a 7-day trend. Some are quietly losing ground.

We track versions, so nobody gets credit for last quarter's weights.

• Point-in-time captures. Recorded when the challenge is created, model version stored alongside. Receipts kept.
• Version tracking. New challenges use the latest version. Old responses are never overwritten.
• Historical preservation. Older outputs stay. Compare then against now: growth arc or regression arc.
• Pricing data. Model pricing on the prices page comes from LiteLLM, updated to current provider rates. Brace your wallet.

Four things we get asked for and keep saying no to.

• No automated benchmarks. No MMLU, no HumanEval. Real people judge, not machines grading themselves.
• No cherry-picking. Outputs ship exactly as the API returns them. If a model fumbles, the fumble ships.
• No pay-for-ranking. Providers can't buy a rank. The one ad slot is sold by email and it never touches a score.
• No synthetic evaluations. Scores come from real votes. We don't let AI grade AI.

OpenAI, Anthropic, Google, DeepSeek, xAI and everyone smaller. If it ships an API, we are already yelling at it.

• Broad coverage. New models go in as soon as they ship a public API. Full roster on the models page.
• Coverage varies. New models have fewer challenges. Rankings firm up as votes come in.

Aggregated, anonymized response and voting data is public. Take it and prove us wrong.

Terminal icon on any response: the exact params, plus a command you can paste. Check our work.

• One-click reproduction. Copy a cURL, Python or raw JSON payload that mirrors the call. No detective work.
• Full parameter transparency. Temperature, system prompt, max tokens, model ID and provider, on every response.
• OpenRouter as common layer. All text models are called through OpenRouter, one API surface to reproduce against, whatever the original provider.