Interest-Based Math Problem Generation
Given a math skill, difficulty, and student interest, generate solvable word problems with verified answers and no irrelevant assumptions.
View token rates · observed 9/11/2026
Compare 2 router rates · observed 9/11/2026
Compare 2 router rates · observed 9/11/2026
All 12 model results and methodology
Generated 100/100 examples
| Model | Tier | Quality | Judged | Scenario cost |
|---|---|---|---|---|
| Nemotron Nano 9B v2 | small | 47% | 100/100 | $31.22 |
| Qwen3 235B A22B | mid | 64% | 100/100 | $117 |
| DeepSeek V3 | mid | 64% | 100/100 | $45.20 |
| Mistral Large 2407 | mid | 49% | 100/100 | $89.62 |
| Arcee Trinity Large Thinking | mid | 35% | 100/100 | $114 |
| GPT-5.4 | frontier | 88% | 100/100 | $558 |
| Claude Opus 4.7 | frontier | 81% | 100/100 | $2011 |
| Gemini 3.1 Pro Preview | frontier | 57% | 100/100 | $2058 |
| Gemma 4 E4B IT | small | 54% | 100/100 | $5.11 |
| Granite 4.1 8B | small | 46% | 100/100 | $7.86 |
| Ministral 8B Instruct 2410 | small | 14% | 100/100 | $8.98 |
| Qwen3 4B Instruct 2507 | small | 42% | 100/100 | $39.15 |
LLM-judge pass rate on 100 synthetic examples. Generator: gpt-5.2. Judge: gpt-5.2. Evaluated 2026-09-09T09:13:02.523Z.
Directional: measured on a synthetic eval set generated by drydock. Cost/latency are not yet captured for taskrouter-run benchmarks.
drydock