What this is, and how it works
Philippa Foot posed the trolley problem in 1967. Now the machines we're handing real decisions to can answer it on demand: instantly, side by side, on any dilemma you invent. This is that experiment.
The lineup
One flagship-tier model from each major lab, current as of July 2026. Every model is reached through a single OpenRouter identifier, so the arena stays honest — same prompt, same parameters, no home-field advantage.
- GPT-5.6OpenAIThe default the world talks to.
- Claude Opus 4.8AnthropicFrontier reasoning, safety-forward.
- Gemini 3.5 FlashGoogleFast, multimodal, everywhere.
- Grok 4.5xAIMaximally curious, minimally filtered.
- Llama 4 MaverickMetaOpen weights, planetary scale.
- DeepSeek V3.2DeepSeekFrontier performance, frugal price.
- Qwen3.7 MaxAlibabaThe East's heavyweight.
- Mistral Medium 3.5MistralEuropean, efficient, no-nonsense.
The prompt
Each model is cast as the switch operator. The framing is deliberately inescapable: the trolley will hit one track, doing nothing is not on the table, and refusing or hedging is disallowed. We ask for a binary — which track to sacrifice — plus two or three sentences of reasoning.
To keep the output structured, the choice is collected through a forced function call (submit_judgment), with a plain-text CHOICE: A/B fallback for any provider that resists tool use. Responses stream token-by-token, which is why you watch the models think rather than just land.
The stack: OpenRouter + Helicone
Every call goes out through Helicone's OpenRouter gateway. OpenRouter gives us one OpenAI-compatible endpoint for all eight models; Helicone wraps it with logging, caching, per-session grouping, and custom properties.
That caching matters here: identical dilemmas return instantly and for free after the first run, which is what makes the live leaderboard practical. If the Helicone key is ever removed, the app falls back to calling OpenRouter directly — nothing breaks, we just lose the observability.
The safety classifier
Trolley problems are about harm, so “someone dies” is the whole point and always allowed. But this is a public toy, so every submitted pairing is first screened by a single fast, cheap model that flags only genuinely not-safe-for-work content — sexual material, gratuitous gore, targeted hate, or self-harm instructions. It fails open: if the classifier is unreachable, your dilemma still runs.
How the leaderboard is scored
The leaderboard runs 6 canonical dilemmas — each with a defensible “minimize the body count” answer — through every model. A model's utilitarian rate is simply how often it takes that head-count call, including the uncomfortable cases where arithmetic collides with rights.
It is a lens on temperament, not a grade. There is no correct answer to the trolley problem; that's rather the point.
A disclaimer, and an invitation
Nothing here is ethical advice, a safety evaluation, or a claim about how these models behave in the wild. It's a thought experiment with a nice interface. Verdicts vary run to run, providers change what ships under a given name, and a clever prompt can push any of these models around.
With that said — go invent a dilemma and see who blinks.