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 11, 2026
Models3
Model coverage3
MetricScore
EvidenceB
Management Consulting Tasks (Internal) Ranking
Higher score ranks better on this benchmark.
| 1 | OP | 43.2% | 100.0% | 3 | C | |
| 2 | OP | 37.2% | 50.0% | 3 | C | |
| 3 | OP | 35.4% | 0.0% | 3 | C |
Management Consulting Tasks (Internal) Score Distribution
A closer view of the leading scores on this benchmark.
Management Consulting Tasks (Internal) Highlights
The leading models and scores on this benchmark.
What is Management Consulting Tasks (Internal)?
What Management Consulting Tasks (Internal) measures and how its scores work.
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. This benchmark is not independently verified and has an evidence level of B.
- Family
- Management Consulting Tasks (Internal)
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- management-consulting-tasks|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
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 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.