Kimi K3 vs MiMo-V2.6-Pro
Verdict
- Kimi K3 (max) leads on quality: 66.5 vs 64.3.
- Kimi K3 (max) is stronger in agents & tools, coding, human preference, long context, maths, multimodal.
- MiMo-V2.6-Pro is stronger in composite, knowledge, reasoning.
- MiMo-V2.6-Pro is 11× cheaper ($0.548 vs $6.00 per 1M blended).
- MiMo-V2.6-Pro streams 1.5× faster (54 vs 37 tokens per second).
| Metric | Kimi K3 (max) | MiMo-V2.6-Pro |
|---|---|---|
| BenchLeader Index | 66.5 | 64.3 |
| Agents & tools score | 67.5 | 55.1 |
| Coding score | 66.2 | – |
| Composite score | 81.5 | 84.8 |
| Human preference score | 68.8 | – |
| Knowledge score | 64.0 | 66.8 |
| Long context score | 70.3 | 69.1 |
| Maths score | 65.3 | – |
| Multimodal score | 64.3 | – |
| Reasoning score | 67.7 | 88.8 |
| Blended price $/M | $6.00 | $0.548 |
| Output speed | 37 tok/s | 54 tok/s |
| Time to first answer | 58.5 s | 39.8 s |
| Context window | 1.0M | 1.0M |
| GPQA Diamond | 93.1% | – |
| FrontierMath Tiers 1–3 | 72.2% | – |
| FrontierMath Tier 4 | 39.0% | – |
| OTIS Mock AIME | 97.2% | – |
| SimpleQA Verified | 50.6% | – |
| SimpleBench | 60.7% | – |
| SciCode | 59.5% | – |
| WeirdML | 82.6% | – |
| LMArena Text | 1485 | – |
| LMArena Hard Prompts | 1514 | – |
| LMArena Coding | 1538 | – |
| LMArena WebDev | 1658 | – |
| LMArena Agent | 6.2 | – |
| AA Intelligence Index | 43.6 | 46.3 |
| AA-LCR | 88.7% | 86.3% |
| MMMU-Pro | 80.5% | – |
| AA-Omniscience | 19.7 | 8.4 |
| GPQA Diamond (AA) | 93.5% | – |
| Humanity's Last Exam (AA) | 46.9% | 49.4% |
| SciCode (AA) | 59.5% | 60.9% |
| LiveCodeBench | 87.2% | – |
| MMLU-Pro | 88.0% | – |
| IOI | 48.9% | – |
| Terminal-Bench 2.1 (Vals) | – | 67.8% |
| Vals Index | – | 59.7 |
| MCP Atlas | 82.3% | – |
| ARC-AGI-1 | 94.5% | – |
| ARC-AGI-2 | 60.4% | – |
| CritPt | 23.4% | 26.6% |
| GDPval (AA) | 51.2% | 58.7% |
| τ²-Bench Banking (AA) | 46.0% | – |
| ITBench SRE (AA) | 47.7% | – |
| Analyst Agent (AA) | 38.8% | – |
| APEX-Agents (AA) | 41.3% | – |
| BioMysteryBench | 71.5% | – |
| Code Migration | 16.1% | 43.0% |
| Excel Modeling Benchmark | 66.4% | 62.9% |
| Finance Agent v2 | – | 58.3% |
| Harvey's Legal Agent Benchmark | 10.8% | 10.8% |
| Legal Research Bench | – | 47.1% |
| Tax Agent Bench | 68.7% | – |
| Terminal-Bench 4.0 (Vals) | 12.6% | – |
| Terminal-Bench Science | 2.9% | 2.9% |
| Time Horizon Index: KSP | 10.5% | – |
| Vibe Code Bench 1-100 | 18.2% | – |
| Vibe Code Bench v1.1 | – | 85.2% |
| FORTRESS | 26.6% | – |
| LMArena Maths | 1501 | – |
| LMArena Creative Writing | 1458 | – |
| LMArena Instruction Following | 1484 | – |
| LMArena Multi-turn | 1496 | – |
| LMArena Longer Queries | 1500 | – |
| Chess Puzzles | 39.0% | – |
| Mystery Game Puzzles | 26.0% | – |
| Surface Evolver Bench | 93.0% | – |
| DeepSWE | 68.5% | – |
| LMCA | 52.7% | – |
| DTBench | 91.2% | – |
| ForecastBench | 61.1% | – |
| ALE-Bench | 1524.5 | – |
| GDP.pdf | 19.0% | – |
| FrontierSWE | 25.9% | – |
| Terminal-Bench 4.0 (AA) | 12.6% | 34.9% |
| Terminal-Bench 2.1 (AA) | 85.0% | – |
| AutomationBench | 58.3% | 58.6% |
| GDP.pdf | 22.0% | 19.2% |
| MLCR | 38.3% | – |
| Harvey LAB | 94.6% | – |
| EnterpriseOps-Gym | 45.3% | – |
| AA-Omniscience: accuracy | 47.6% | 34.9% |
| AA-Omniscience: non-hallucination | 46.8% | 59.4% |
| AA-Briefcase | 1510 | 1522 |
| AA Openness Index | 38.9 | – |
Data as of 2026-09-23. Best configuration of each model; every score links to its source on the model pages.
Kimi K3 vs MiMo-V2.6-Pro: questions
- Is Kimi K3 better than MiMo-V2.6-Pro?
- Kimi K3 (max) leads on quality: 66.5 vs 64.3. The BenchLeader Index combines every independent quality benchmark; Kimi K3 (max) is ahead overall as of 2026-09-23, but check the category scores for your use.
- Is Kimi K3 better than MiMo-V2.6-Pro for agentic tasks?
- Kimi K3 scores higher in agentic tasks (68 vs 55 on the category index, where 50 is average).
- Which is cheaper, Kimi K3 or MiMo-V2.6-Pro?
- MiMo-V2.6-Pro is cheaper: $0.548 against $6.00 per million tokens, blended at three input tokens per output token.
- Which is faster, Kimi K3 or MiMo-V2.6-Pro?
- MiMo-V2.6-Pro streams faster: 54 against 37 output tokens per second.
- Which has the larger context window?
- Both accept 1.0M tokens of context.