Sansa Bench
Applied mathematics leaderboard for Sansa Bench, with charts, model comparison, and methodology. This dimension covers math applied to practical scenarios, including modeling and optimization problems.
Top models for Applied Mathematics
- 1.
Gpt-5.4 Reasoning Low0.906 - 2.
Gemini-3.1-Pro-Preview Reasoning Low0.903 - 3.
Claude-Opus-5 Reasoning High0.903 - 4.Gemini-3-Flash-Preview Reasoning High0.896
- 5.Gemini-3.1-Pro-Preview Reasoning High0.891
Methodology: Applied Mathematics
What it measures
Tests applied mathematics problems and real-world applications. Queries require mathematical reasoning applied to practical scenarios, including optimization problems, modeling, and mathematical problem-solving in context.
Scoring & Criteria
For numeric questions: returns score 1.0 if the extracted numeric value matches any acceptable answer format within the specified tolerance (evaluation_criteria.tolerance), otherwise 0.0. When the answer field contains an array, the model's response must match one of the values in the array. Tolerance can be absolute or relative when specified. For multiple choice questions: returns score 1.0 if the extracted answer letter exactly matches the expected answer (after normalization), otherwise 0.0. The system prompt requests answers in `<answer>X</answer>` format where X is a letter from the provided choices. The grader normalizes for models that include the full choice text instead of just the letter, or that violate the answer tag format.
Evaluation Type: Numeric / Multiple Choice
Uses both numeric matching for open-ended problems and exact match for multiple choice questions. Some numeric questions accept multiple answer formats with different units (e.g., when the answer field contains an array like ["0.2352 m", "23.52 cm"]), while others require a single numeric value. Multiple choice questions use exact string matching.