Task
Return valid JSON that matches a schema
Anything that calls a model from code needs parseable output. Prose wrapped around it breaks the caller.
- Measured
- 2026-09-12 UTC
- Result
- 6 of 6 passed
- Temperature
- 0
- Prompt size
- 148 chars
| Model | Result | Time | Thinking tokens | What came back | |
|---|---|---|---|---|---|
| gemini-2.5-flash-lite | pass | 912ms | not reported | population=9770000 | |
| gemini-3.1-flash-lite | pass | 923ms | not reported | population=9776000 | |
| gemini-3.5-flash-lite | pass | 1,019ms | not reported | population=9776000 | |
| gemini-2.5-flash | pass | 2,107ms | 252 | population=9700000 | |
| gemini-3-flash-preview | pass | 2,147ms | 228 | population=9776000 | |
| gemini-3.5-flash | pass | 2,388ms | 398 | population=9776000 |
What happened
Every model passed
All 6 models we could reach completed this one. The difference is not capability, it is what each spent to get there.
Thinking more did not mean getting it right
On this task gemini-3.5-flash spent 398 thinking tokens and passed. 3 models passed without reporting a single thinking token. Six models is a small sample, so read this as what happened here, not as a law.
2.6× between fastest and slowest
gemini-2.5-flash-lite finished in 912ms. gemini-3.5-flash took 2,388ms for the same prompt.
The exact prompt
Return only JSON with exactly these keys: {"city": string, "population": number, "country": string}. The city is Seoul. No markdown, no explanation.
Pass/fail is decided by code, not by reading the answer. The check for this task is in bench/tasks.mjs, and failed responses are stored verbatim so the verdict can be re-read.