reasoning benchmark
Management Consulting Tasks (Internal)
Management Consulting Tasks is an internal OpenAI evaluation of long-horizon professional knowledge work drawn from management-consulting workflows, scoring whether models produce correct, decision-ready analyses.
Updated Aug 7, 2026
Published models3
Registry coverage3
MetricScore
EvidenceB
Management Consulting Tasks (Internal) leaderboard
Sorted by the source-provided rank. Higher score is better according to the registry.
| 1 | OP | 43.2% | 100.0% | 3 | C | |
| 2 | OP | 37.2% | 50.0% | 3 | C | |
| 3 | OP | 35.4% | 0.0% | 3 | C |
Score distribution
Top published rows on the benchmark's original scale.
Management Consulting Tasks (Internal) highlights
The top published results on this benchmark's own scale.
What is Management Consulting Tasks (Internal)?
Definition and scoring fields from the benchmark registry.
Management Consulting Tasks is an internal OpenAI evaluation of long-horizon professional knowledge work drawn from management-consulting workflows, scoring whether models produce correct, decision-ready analyses.
Scores are shown in ratio. The current registry marks this benchmark as not independently verified with evidence level B.
- Family
- Management Consulting Tasks (Internal)
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- management-consulting-tasks|llm-stats-current
Source-native results are preserved. Eligibility for the overall LLMBoard score is a separate policy decision.
FAQ
Common questions about Management Consulting Tasks (Internal).
Which model scores highest on Management Consulting Tasks (Internal)?
GPT-5.6 Sol is currently ranked first with 43.2%.
What does Management Consulting Tasks (Internal) measure?
Management Consulting Tasks is an internal OpenAI evaluation of long-horizon professional knowledge work drawn from management-consulting workflows, scoring whether models produce correct, decision-ready analyses.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
3 unique published model results are currently shown.
Does this benchmark affect the overall score?
This benchmark is preserved as source-native evidence but is not eligible for the current overall score.