Independent comparison of LLMs across 8 management task categories
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GPT-5.6 Sol
Kimi K3
MiniMax M3The top of the rating – GPT-5.6 Sol, Kimi K3 and GPT-5.6 Terra – differ by less than 0.3 points: within measurement error, which makes it a statistical tie. The leader is reachable from Russia only via VPN, while Kimi K3 from the same top cluster works directly – no need to route around blocks.
Chinese models top what's reachable without a VPN: Kimi K3 (#2), MiniMax M3 (#8), MiMo v2.5 Pro (#9), Kimi K2.6 (#12). All work from Russia directly, and Kimi K3 is statistically on par with the global leader.
Russian models: DeepSeek V4 Flash on Yandex Cloud (#32), GigaChat 3.5 Ultra (#37), Alice AI (#43). Directly accessible, but noticeably behind the leaders – including on Russia-specific questions.
The best value comes from Chinese open-weight models: MiniMax M3 (~$0.01 per test), DeepSeek V4 Flash (<$0.01). Flagships GPT-5.6 Sol, Kimi K3 and Claude Opus run $0.2–0.3 per test – 20–30× more for a fraction of a point. And the same DeepSeek V4 Flash costs ~27× more on Yandex Cloud than via OpenRouter – now IP-blocked in Russia.
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. The two judges differ in absolute generosity (Gemini scores systematically higher), but they agree strongly on ranking (correlation ~0.95); because both score every model with equal weight, that constant offset cancels out of the comparison, so no separate bias correction is applied.
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. Two-judge limit: both are large proprietary models, so a bias shared by both would not be detected, and each score reflects a single model run – treat small gaps with caution.
Each dot is a ranked model. Horizontal – cost per test (log scale), vertical – score. The sweet spot is top-left: cheap and high-ranked. Hover a dot for details, click to open its page.
GPT-5.6 Sol
≈ Kimi K3
≈ Kimi K3
≈ Kimi K3
≈ GPT-5.6 Sol
≈ Kimi K3
≈ GPT-5.6 Sol
≈ GPT-5.6 SolModels in the same tier (gap under half a point) are equivalent in practice – order within a tier is not meaningful. Choose by availability and price.
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| Grasps instantly | 8.6–9.0 | Open | |
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| Digs into details | 7.6–8.4 | Open | |
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| Follows clear tasks | 6.6–7.5 | Open | |
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| Needs supervision | 6.0–6.3 | Open | |
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| Gets confused easily | 4.2–4.8 | Open | |
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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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