Everything you need to know about ai models are terrible at betting.
[ad_1]“Every frontier model we evaluated lost money over the season and many experienced ruin,” the authors of the paper concluded, with the AI “systematically underperforming humans” in this scenario.
| AI Model | Mean ROI | Best try | Worst try | Mean final bankroll |
|---|---|---|---|---|
| Anthropic Claude Opus 4.6 | –11.0% | –0.2% | –18.8% | £89,035 |
| OpenAI GPT-5.4 | –13.6% | –4.1% | –31.6% | £86,365 |
| Google Gemini 3.1 Pro | –43.3% | +33.7% | –100.0% | £56,715 |
| Google Gemini Flash 3.1 LP | –58.4% | +24.7% | –100.0% | £41,605 |
| Z.AI GLM-5 | –58.8% | –14.3% | –100.0% | £41,221 |
| Moonshot Kimi K2.5 | –68.3% | –27.0% | –100.0% | £7,420 |
| xAI Grok 4.20 | –100.0% | –100.0% | –100.0% | £0 |
| Acree Trinity | –100.0% | –100.0% | –100.0% | £0 |
| Each model began with a £100,000 normalized bankroll. Return on investment and final bankroll are averaged across three tries. Grok and Trinity did not complete every attempt. | ||||
The results offer some comfort to white-collar professionals and businesses who are fretting that AI could take their jobs, as it roils the shares of industries from finance to marketing.
Ross Taylor, one of the study’s authors and General Reasoning’s chief executive, said: “There is so much hype about AI automation, but there’s not a lot of measurement of putting AI into a longtime horizon setting.”
He added that many of the benchmarks typically used to test AI are flawed because they are set in “very static environments” that bear little resemblance to the chaos and complexity of the real world.
General Reasoning’s paper, which has not yet been peer reviewed, provides a counterweight to growing excitement in Silicon Valley about the huge recent leaps in AI’s ability to complete computer programming tasks with little to no human intervention.
Taylor, a former Meta AI researcher, said: “If you… try AI on some real-world tasks, it does really badly… Yes, software engineering is very important and economically valuable, but there are lots of other activities with longer time horizons that are important to look at.”
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Frequently Asked Questions
Every frontier model evaluated lost money over the season and many experienced ruin, systematically underperforming humans.
xAI's Grok 4.20 and Acree Trinity both lost everything – -100% ROI with a £0 final bankroll from a £100,000 starting stake.
Anthropic's Claude Opus 4.6, with -11.0% mean ROI and a £89,035 final bankroll – though still a loss.
Per author Ross Taylor, typical AI benchmarks use "very static environments" unlike real-world chaos; on long-horizon real-world tasks, AI "does really badly."
