--- 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 the rows that are both worse and dearer. No cut of inference, no affiliate, no paid placement. image: "https://lenvanderhof.com/media/generated/blog-hero-undominated-frontier-crates-v1.87319fd6d2cd.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 the models that are both worse and dearer. Len P. van der HofPublished 25 August 20264 min read Eleven on the edge. The rest of the pile is both worse and dearer. Direct answer Undominated.ai is an independent AI inference price index. It ranks models on independently measured capability first. Price breaks ties. A model that is both worse and dearer is named as dominated. Unrated is not zero. On 25 August 2026 the live board held 409 models from 50 providers; of 108 rated, priced rows, 97 were beaten on quality and undercut on price, 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 worse-and-dearer row. - A model is dominated when something else is better and cheaper and 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 is both worse and dearer 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. Two sources sit side by side and are never blended: Artificial Analysis indices, shown for evaluation, and LMArena human preference, used under CC BY 4.0 from the official dataset. The site does not score models itself. Where the two sources part company, that disagreement is the finding. A composite would erase it. ## Why an average is the wrong object The spread between the cheapest and the dearest model in the catalogue is about **15,000×**. 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 worse-and-dearer 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 model in the catalogue scores higher *and* costs less *and* can still do what it can do: same context class, same modalities, same tools. Raw two-axis Pareto lies often. The [methodology](https://undominated.ai/methodology/) reserves “better and cheaper” for a replacement whose capability envelope is a superset. If you would give something up, the board says so. A model is **on the value frontier** when nothing both beats it and undercuts it 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 beaten on quality *and* undercut on price - **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. ## 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", 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