reasoning benchmark
OpenBookQA Leaderboard
OpenBookQA is a question-answering dataset modeled after open book exams for assessing human understanding. It contains 5,957 multiple-choice elementary-level science questions that probe understanding of 1,326 core science facts and their application to novel situations, requiring combination of open book facts with broad common knowledge through multi-hop reasoning.
Updated Aug 17, 2026
Models5
Model coverage5
MetricScore
EvidenceB
OpenBookQA Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelMI | Score89.6% | Percentile100.0% | Participants5 | EvidenceC | Evaluated |
| Rank02 | ModelMI | Score79.2% | Percentile75.0% | Participants5 | EvidenceC | Evaluated |
| Rank03 | ModelMI | Score79.2% | Percentile50.0% | Participants5 | EvidenceC | Evaluated |
| Rank04 | ModelMA | Score60.6% | Percentile25.0% | Participants5 | EvidenceC | Evaluated |
| Rank05 | ModelNR | Score49.4% | Percentile0.0% | Participants5 | EvidenceC | Evaluated |
OpenBookQA Highlights
The leading models and scores on this benchmark.
OpenBookQA Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for OpenBookQA
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis openbookqa AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01MIPhi-3.5-MoE-instructMicrosoft
- Score
- 89.6%
Strengths
- Ranks #1 of 5 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures OpenBookQA, not total model capability
- 02MIPhi-3.5-mini-instructMicrosoft
- Score
- 79.2%
- Speed
- Up to 23 tok/s via Azure
Strengths
- Ranks #2 of 5 compared models
- 75th percentile on this benchmark
- C evidence result
Considerations
- This result measures OpenBookQA, not total model capability
- 03MIPhi 4 MiniMicrosoft
- Score
- 79.2%
- Price
- $0.07 input / $0.30 output per 1M tokens
Strengths
- Ranks #3 of 5 compared models
- 50th percentile on this benchmark
- C evidence result
Considerations
- This result measures OpenBookQA, not total model capability
- 04MAMistral NeMo InstructMistral AI
- Score
- 60.6%
- Price
- $0.15 input / $0.15 output per 1M tokens
- Speed
- Up to 42 tok/s via Google
Strengths
- Ranks #4 of 5 compared models
- 25th percentile on this benchmark
- C evidence result
Considerations
- This result measures OpenBookQA, not total model capability
- 05NRHermes 3 70BNous Research
- Score
- 49.4%
Strengths
- Ranks #5 of 5 compared models
- 0th percentile on this benchmark
- C evidence result
Considerations
- This result measures OpenBookQA, not total model capability
Selection summary
Best AI Models for OpenBookQA
Phi-3.5-MoE-instruct currently leads OpenBookQA with 89.6%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
What is OpenBookQA?
What OpenBookQA measures and how its scores work.
OpenBookQA is a question-answering dataset modeled after open book exams for assessing human understanding. It contains 5,957 multiple-choice elementary-level science questions that probe understanding of 1,326 core science facts and their application to novel situations, requiring combination of open book facts with broad common knowledge through multi-hop reasoning.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- OpenBookQA
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- openbookqa|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about OpenBookQA.
Which model scores highest on OpenBookQA?
Phi-3.5-MoE-instruct is currently ranked first with 89.6%.
What does OpenBookQA measure?
OpenBookQA is a question-answering dataset modeled after open book exams for assessing human understanding. It contains 5,957 multiple-choice elementary-level science questions that probe understanding of 1,326 core science facts and their application to novel situations, requiring combination of open book facts with broad common knowledge through multi-hop reasoning.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
5 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.