--- title: "Introducing Undominated.ai | Independent AI inference price index | Len P. van der Hof" description: Undominated.ai ranks AI models by independently measured capability first, then by price. It names every row another model beats without a trade-off. No cut… image: "https://lenvanderhof.com/media/generated/blog-hero-undominated-dual-witness-lockup-v3.8c5dbe530313.wide.webp" --- [AI Systems](https://lenvanderhof.com/en/blog/category/ai-systems/) Research guide # Introducing Undominated.ai: the independent AI inference price index Best first. Then price. The board that names every model something else beats without a trade-off. Len P. van der HofPublished 25 August 2026Updated 26 September 20264 min read Best first. Then price. Direct answer Undominated.ai is an independent AI inference price index. It ranks models on independently measured capability first. Price breaks ties. A model is named as dominated when another scores at least as high, costs no more, and is strictly better on one of the two. Unrated is not zero. On 25 August 2026 the live board held 409 models from 50 providers; of 108 rated, priced rows, 97 were dominated and 11 were not. Those eleven are the value frontier. The site takes no cut of inference, no affiliate, and no paid placement. Snapshot numbers move. The live board is the source. ## Key takeaways - Quality first, then price. A blended value score hides the dominated row. - A model is dominated when something else scores at least as high for no more money and wins on at least one of the two. The board then says whether the replacement can still do the job. - Unrated is not a failed score. Most of the catalogue has no independent quality number. - No cut of inference. No affiliate. No paid placement. Corrections go through a public GitHub issue with a primary source. You already have a model in production. Someone on the team found a cheaper endpoint. The spreadsheet treats that as a win. It is not a win if the cheaper row cannot do the job, and it is not a win if a third row is both stronger and cheaper than the one you kept. [Undominated.ai](https://undominated.ai/) is the index I built for that decision. Capability first. Price second. The row that another model beats, on score or on price without losing on the other, gets named. ## What it is The public line is short on purpose: **Undominated.ai: the AI price index.** Best first. Then price. It is not a router. It does not sell tokens. It does not take a percentage of inference. It does not put a paid badge on a row. The [independence page](https://undominated.ai/independence/) is the commercial boundary in one screen. Revenue in v1 is none. A later paid feed, if it exists, would sell history and provenance, not a better rank. Capability comes from independent evaluators. Every published score is LMArena Elo from human preference, used under CC BY 4.0 from the official dataset. Artificial Analysis figures are not published: the site holds no redistribution licence, so they serve as an internal cross-check and never reach a page, an export, or the API. The site does not score models itself and never blends evaluators into one number. ## Why an average is the wrong object On 23 September 2026 the methodology page listed the cheapest model in the catalogue as **8,824×** cheaper than the dearest. That is not a rounding error. It is why a single “value” number is a marketing instrument. Blend quality and price into one score and the dominated row can hide behind an attractive ratio. Quality-per-dollar, run on this catalogue, crowns cheap models near the floor of the scale. Nobody should ship those as “best value.” Other public indexes exist. Some publish a geometric-mean blended $/M. Some chain SKUs like a commodity index. Some weight lab tokens by transacted volume. They are answering a different question. This one asks which models are still worth considering at all, then what the job costs under a workload you can see. ## What “undominated” means A model is **dominated** when another rated, priced model in the catalogue scores at least as high, costs no more, and is strictly better on at least one of the two. That two-axis test is what the board counts. Raw two-axis Pareto still lies often: a model can score higher and cost less while accepting no images, capping output, or holding far less context. So the [methodology](https://undominated.ai/methodology/) calls a dominating model a clean replacement only when it keeps at least the current model’s context window, maximum output, input types, tool use and reasoning. If you would give something up, the board says so. A model is **on the value frontier** when nothing scores at least as high for less, or higher for the same price, under the selected lens and workload. Chartreuse in the interface is reserved for that membership. It is not a highlight colour for sale. Ranks are **significance ranks**, the way [LMArena’s Rank (UB)](https://news.lmarena.ai/ranking-method/) has worked for years. Models the measurement cannot separate share a rank. “The #1 model” is not a claim this data supports. Ties are ties. Unrated is not zero. Most of the catalogue has no independent quality score. Those rows are listed by price and kept out of quality order. Not measured is not the same as measured badly. ## A snapshot, not a monument On **25 August 2026** the live board reported: - **409** models, **50** providers, **55** with tiered pricing - **97 of 108** rated, priced models dominated - **11** not. That set is the frontier. Those numbers move. Workload shape moves them. Batch delivery moves them. A new fetch moves them. Cite the live page, not this paragraph. Headline $/M is often the wrong number. Context tiers change the rate past a prompt length. Some models bill reasoning tokens on a separate meter. A few discount by time of day. The board reprices the row when the workload you selected crosses those lines. ## How to use it this week 1. Open the [leaderboard](https://undominated.ai/). Set the lens and the workload to the job you actually run. 2. Open the [frontier](https://undominated.ai/frontier/). That is the short list. 3. [Check the model you already pay for](https://undominated.ai/check/). If it is dominated, the board names what beats it and what you would give up. 4. Read the [methodology](https://undominated.ai/methodology/) before you treat a rank as a purchase order. 5. If a live figure disagrees with a primary source, [file a correction](https://github.com/Lenvanderhof/Undominated.ai/issues/new?template=wrong-price.yml). The public GitHub repo is the tracker, not a second copy of the catalogue. English is the source language. Locales ship as machine translation with numbers, model names, and provider names left untouched. If a cheaper endpoint cannot do the job, it was never cheaper. If something else is both stronger and cheaper, keeping the incumbent is a preference, not a cost argument. Put the preference on the table. Then look at the eleven. Cite this:Introducing Undominated.ai: the independent AI inference price index.Len P. van der Hof. [https://lenvanderhof.com/en/blog/introducing-undominated/](https://lenvanderhof.com/en/blog/introducing-undominated/) · Published 25 August 2026. ## Sources 1. [Undominated.ai](https://undominated.ai/) 2. [Methodology](https://undominated.ai/methodology/) 3. [Independence](https://undominated.ai/independence/) 4. [Public correction tracker](https://github.com/Lenvanderhof/Undominated.ai) 5. [LMArena ranking method (Rank UB)](https://news.lmarena.ai/ranking-method/) · LMArena ## Further reading - [Undominated.ai](https://undominated.ai/) - [Methodology](https://undominated.ai/methodology/) - [Independence](https://undominated.ai/independence/) - [Report a wrong figure](https://github.com/Lenvanderhof/Undominated.ai/issues/new?template=wrong-price.yml) - [Evaluate the reasoning, not the fluency](https://lenvanderhof.com/en/blog/evaluate-reasoning-not-fluency/) - [What is an AI agent?](https://lenvanderhof.com/en/blog/what-is-an-ai-agent/) About the author ## [Len P. van der Hof](https://lenvanderhof.com/en/authors/len-p-van-der-hof/) Entrepreneur, AI Innovator and Venture Builder Len P. van der Hof builds practical AI systems, digital ventures and evidence-informed tools for founders. ```json { "@context": "https://schema.org", "@graph": [ { "@type": "Person", "@id": "https://lenvanderhof.com/#person", "name": "Len P. van der Hof", "alternateName": [ "Len van der Hof", "L.P. van der Hof", "Leendert Pieter van der Hof" ], "honorificSuffix": "MSc", "url": "https://lenvanderhof.com/", "image": [ "https://lenvanderhof.com/photos/len-portrait-1.jpg", "https://lenvanderhof.com/photos/len-portrait-2.jpg", "https://lenvanderhof.com/photos/len-portrait-3.jpg", "https://lenvanderhof.com/photos/len-portrait-4.jpg", "https://lenvanderhof.com/photos/len-speaking.jpg", "https://lenvanderhof.com/photos/len-hero.jpg" ], "jobTitle": "Entrepreneur, AI Innovator and Venture Builder", "description": "Len P. van der Hof, MSc, is a Dutch entrepreneur and AI innovator in Zwijndrecht. 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