Which AI is the best partner for an ambitious person? We test frontier models on the actual work of building something — strategy, finance, legal, negotiation, marketing, fundraising, execution, and integrity under pressure — and rank them here.
Disclaimer: These are simply our own findings from our own independent tests, published for your reference. We are not affiliated with, sponsored by, or endorsed by any AI lab, and nothing here is an official claim about any model's capabilities. Scores reflect our methodology and question set at the time of testing; your results and experience may differ. This page is for informational purposes only and is not professional, legal, or financial advice.
Most AI benchmarks measure trivia, puzzles, or code. This one measures the job an ambitious person actually hires an AI for: making money decisions, reading contracts, closing deals, and staying honest under pressure. Every model takes the exact same 172-item private exam at temperature 0 — same questions, same order, no retries — and the total is a weighted score out of 100.
| Section | Weight | Items | What it tests |
|---|---|---|---|
| Strategy | 15% | 25 | Market entry, pivots, pricing, prioritization — real cases with real numbers, judged like a top operator would |
| Finance | 15% | 40 | Unit economics, CAC/LTV, runway, break-even, cap tables — every answer is a number checked against the math |
| Legal | 15% | 30 | Spotting red flags in real contract language — liability traps, IP overreach, auto-renewals — plus judgment calls like co-founder splits |
| Negotiation | 12% | 12 | Live multi-turn deals — sales, leases, term sheets — against a counterparty with hidden walk-away numbers |
| Marketing | 10% | 25 | Funnel math, channel strategy, positioning, and diagnosing exactly which stage of a funnel is broken |
| Fundraising | 10% | 20 | SAFE conversions, dilution, liquidation waterfalls, and catching predatory term-sheet clauses |
| Execution | 13% | 5 | Big multi-deliverable tasks — launch plans, turnarounds, acquisitions, crisis response — graded on completeness and whether the numbers add up |
| Integrity | 10% | 15 | Pressure scenarios that tempt the model to fudge metrics, backdate documents, or build on a false premise |
About 40% of the score is objective. The finance, fundraising, and marketing-math items have a single correct number, computed and verified in code. The model either gets it right or it doesn't — no AI opinion involved.
The rest is judged blind by a two-model panel from different AI labs. Judges score against written rubrics with anchored examples of what a 2, 5, 8, and 10 look like — and they never know which model wrote the answer. When the two judges disagree significantly on an answer, a third judge from another lab is called in and the median score wins, so no single judge's bias can move the board. Negotiations and execution tasks — where runs genuinely diverge — are run twice and averaged. Every answer under 500 words: concision under constraint is part of the test.
Negotiations are played live. The model being tested negotiates over multiple turns against a counterparty AI with secret instructions: a hidden walk-away price and specific triggers for when it will concede. Scoring is 60% outcome — did it hit the targets, protect the terms that mattered, walk away from a bad deal — and 40% process, like trading concessions instead of giving them away. Some scenarios are designed so the only winning move is to walk away.
Integrity cuts both ways. Models earn points for refusing genuinely bad asks — dressing up metrics for investors, backdating an option grant — while still offering the honest alternative. But they lose points for over-refusing: several scenarios sound aggressive yet are perfectly legal, and the right answer is to just help.
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