Independent comparison of LLMs across 8 management task categories
Claude Opus 4.6 leads (8.93), followed by GPT-5.5 (8.76), MiMo v2.5 Pro (8.51), Claude Opus 4.7 (8.48) and Kimi K2.6 (8.43) – five models in the elite cluster. The difference of < 0.50 within a cluster is not statistically significant.
Chinese models hold strong positions: MiMo v2.5 Pro (#3), Kimi K2.6 (#5), Qwen 3.6 Plus (#7). All accessible from Russia directly. 12 of 27 models work in Russia without VPN.
Russian models tested in v2: Alice AI LLM (Yandex) – #25 (6.24), GigaChat 2 Max (Sber) – #26 (4.23). Both lag far behind the leaders, especially in regional awareness – a paradoxically weak category.
Claude Opus 4.6 leads in 7 of 8 categories: analysis, planning, problem-solving, team management, communication, learning, and regional context. Information search – GPT-5.5. Models within 0.50 points are considered equivalent.
All models were tested with prompts written by a real manager – no prompt engineering. This shows how each tool works out of the box. 10 scenarios per category provide statistically significant conclusions.
All models solved 80 scenarios in Russian (10 per each of 8 categories) – tasks typical for a middle manager (team of 5–30 people). Prompts were written as a real manager writes – no optimization, no special techniques.
Each response was evaluated by two independent LLM judges: Claude Opus 4.6 and Gemini 3.1 Pro with equal weight (50/50). Scoring scale 1–10. No bias correction needed – judges showed high agreement without systematic biases.
Scale: 1.0–10.0 (10 scenarios per category)
Models in the same cluster (gap < 0.50) are considered equivalent. Between-cluster differences are statistically significant (ANOVA p < 0.001 in all 8 categories). V2 methodology: 10-point scale, 10 scenarios per category, two judges with equal weight.
| Tier | Model | Score | |
|---|---|---|---|
| Elite | 8.77 | Open | |
| 8.66 | Open | ||
| Strong | 8.37 | Open | |
| 8.32 | Open | ||
| 8.27 | Open | ||
| 8.18 | Open | ||
| 7.94 | Open | ||
| 7.82 | Open | ||
| 7.77 | Open | ||
| 7.75 | Open | ||
| 7.66 | Open | ||
| 7.65 | Open | ||
| 7.60 | Open | ||
| 7.60 | Open | ||
| 7.58 | Open | ||
| Average | 7.45 | Open | |
| 7.38 | Open | ||
| 7.33 | Open | ||
| 7.29 | Open | ||
| 7.26 | Open | ||
| 7.13 | Open | ||
| 6.86 | Open | ||
| 6.86 | Open | ||
| 6.84 | Open | ||
| 6.63 | Open | ||
| Below Average | 6.24 | Open | |
| 6.04 | Open | ||
| Weak | 4.83 | Open | |
| 4.20 | Open |
March 2026 · 54 models · Scale 1–5 · Claude Opus 4.5 (70%) + Gemini 3 Pro (30%) with bias correction. Includes Russian models (YandexGPT, GigaChat).
| # | Model | Score |
|---|---|---|
| 1 | 7.58 | |
| 2 | 4.94 | |
| 3 | 4.85 | |
| 4 | 4.79 | |
| 5 | 4.78 | |
| 6 | 4.78 | |
| 7 | 4.74 | |
| 8 | 4.69 | |
| 9 | 4.69 | |
| 10 | 4.63 | |
| 11 | 4.62 | |
| 12 | 4.57 | |
| 13 | 4.56 | |
| 14 | 4.55 | |
| 15 | 4.50 | |
| 16 | 4.48 | |
| 17 | 4.46 | |
| 18 | 4.42 | |
| 19 | 4.42 | |
| 20 | 4.41 | |
| 21 | 4.39 | |
| 22 | 4.33 | |
| 23 | 4.32 | |
| 24 | 4.29 | |
| 25 | 4.29 | |
| 26 | 4.28 | |
| 27 | 4.25 | |
| 28 | 4.24 | |
| 29 | 4.22 | |
| 30 | 4.14 | |
| 31 | 4.14 | |
| 32 | 4.13 | |
| 33 | 4.11 | |
| 34 | 4.05 | |
| 35 | 4.03 | |
| 36 | 4.00 | |
| 37 | 3.97 | |
| 38 | 3.86 | |
| 39 | 3.75 | |
| 40 | 3.67 | |
| 41 | 3.58 | |
| 42 | 3.27 | |
| 43 | 3.26 | |
| 44 | 3.15 | |
| 45 | 3.13 | |
| 46 | 3.08 | |
| 47 | 3.08 | |
| 48 | 3.05 | |
| 49 | 2.95 | |
| 50 | 2.90 | |
| 51 | 2.85 | |
| 52 | 2.82 | |
| 53 | 2.61 | |
| 54 | 2.27 |
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