Model comparison
Kimi K2 (Jul 2025) vs MiMo-V2-Omni
MiMo-V2-Omni is the stronger model overall, scoring 42.9 to 40.9 on the Noometry Index.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. Kimi K2 (Jul 2025) scores higher in 3 categories and MiMo-V2-Omni in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where MiMo-V2-Omni leads 28.6 to 22.7.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.57 / $2.30 for Kimi K2 (Jul 2025).
- Kimi K2 (Jul 2025) has downloadable open weights; the other is API-only.
Side by side
| Kimi K2 (Jul 2025) | MiMo-V2-Omni | |
|---|---|---|
| Provider | Moonshot AI | Xiaomi |
| Noometry Index | 40.9 | 42.9 |
| Released | 2025-07-12 | 2026-03-18 |
| Weights | Open | Proprietary |
| Context window | 262K | 262K |
| Max output | 262K | 131K |
| Input $ / M tokens | $0.57 | $0.14 |
| Output $ / M tokens | $2.30 | $0.28 |
| Results tracked | 42 | 18 |
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Category by category
Coding Too close to call
Kimi K2 (Jul 2025): 43.1 (#83), MiMo-V2-Omni: 42.7 (#87)
| Benchmark | Kimi K2 (Jul 2025) | MiMo-V2-Omni |
|---|---|---|
| LMArena Coding | 1399 | 1467 |
| SWE-bench Verified (bash only) | 63.4% | — |
| Aider Polyglot | 59.1% | — |
| GSO | 4.9% | — |
| WeirdML | 42.8% | — |
| ALE-Bench | 597.5 | — |
Agentic & Tool Use Not comparable
Kimi K2 (Jul 2025): 32.2 (#59), MiMo-V2-Omni: —
| Benchmark | Kimi K2 (Jul 2025) | MiMo-V2-Omni |
|---|---|---|
| Terminal-Bench | 35.7% | — |
| Berkeley Function Calling Leaderboard | 59.1% | — |
| METR Time Horizons | 59.2% | — |
Reasoning MiMo-V2-Omni leads
Kimi K2 (Jul 2025): 22.7 (#173), MiMo-V2-Omni: 28.6 (#86)
| Benchmark | Kimi K2 (Jul 2025) | MiMo-V2-Omni |
|---|---|---|
| LMArena Hard Prompts | 1384 | 1445 |
| SimpleBench | 26.3% | — |
| Kagi LLM Benchmark | 64.4% | — |
| Epoch Capabilities Index | 146.02 | — |
| ForecastBench | 60.2 | — |
Math Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 40.1 (#81), MiMo-V2-Omni: 36.4 (#112)
| Benchmark | Kimi K2 (Jul 2025) | MiMo-V2-Omni |
|---|---|---|
| LMArena Math | 1396 | 1432 |
| Omni-MATH | 65.4% | — |
| FrontierMath (Feb 2025 set) | 21.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge MiMo-V2-Omni leads
Kimi K2 (Jul 2025): 36.9 (#153), MiMo-V2-Omni: 39.9 (#114)
| Benchmark | Kimi K2 (Jul 2025) | MiMo-V2-Omni |
|---|---|---|
| LMArena Expert | 1363 | 1449 |
| MMLU-Pro | 81.9% | — |
| Confabulations | 20.4% | — |
| Vectara Hallucination Rate | 17.9% | — |
| GPQA (HELM) | 65.3% | — |
Multimodal Not comparable
Kimi K2 (Jul 2025): —, MiMo-V2-Omni: 37.9 (#62)
| Benchmark | Kimi K2 (Jul 2025) | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | — | 1228 |
Multilingual MiMo-V2-Omni leads
Kimi K2 (Jul 2025): 49.8 (#125), MiMo-V2-Omni: 52.0 (#97)
| Benchmark | Kimi K2 (Jul 2025) | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | 1372 | 1404 |
| LMArena Chinese | 1416 | 1469 |
| LMArena French | 1379 | 1448 |
| LMArena German | 1386 | 1398 |
| LMArena Japanese | 1349 | 1318 |
| LMArena Korean | 1324 | 1355 |
| LMArena Russian | 1384 | 1412 |
| LMArena Spanish | 1383 | 1432 |
Instruction Following MiMo-V2-Omni leads
Kimi K2 (Jul 2025): 71.3 (#151), MiMo-V2-Omni: 75.4 (#62)
| Benchmark | Kimi K2 (Jul 2025) | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | 1347 | 1428 |
| IFEval | 85% | — |
Long Context MiMo-V2-Omni leads
Kimi K2 (Jul 2025): 41.2 (#140), MiMo-V2-Omni: 44.1 (#72)
| Benchmark | Kimi K2 (Jul 2025) | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | 1353 | 1442 |
| Fiction.LiveBench | 66.7% | — |
| CL-bench | 17.6% | — |
Writing & Preference Too close to call
Kimi K2 (Jul 2025): 62.5 (#76), MiMo-V2-Omni: 61.6 (#83)
| Benchmark | Kimi K2 (Jul 2025) | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | 1380 | 1424 |
| LMArena Creative Writing | 1349 | 1393 |
| LMArena Multi-Turn | 1371 | 1446 |
| Short-Story Creative Writing | 85.6% | — |
| EQ-Bench Creative Writing | 1666 | — |
| WildBench | 86.2% | — |
Frequently asked questions
Is Kimi K2 (Jul 2025) better than MiMo-V2-Omni?
MiMo-V2-Omni is the stronger model overall, scoring 42.9 to 40.9 on the Noometry Index.
Which is cheaper, Kimi K2 (Jul 2025) or MiMo-V2-Omni?
MiMo-V2-Omni is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; Kimi K2 (Jul 2025) lists at $0.57 and $2.30.
Is Kimi K2 (Jul 2025) or MiMo-V2-Omni better for coding?
They score almost the same on coding (43.1 vs 42.7); test both on your own repository before choosing.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do Kimi K2 (Jul 2025) and MiMo-V2-Omni share?
17 benchmarks have published results for both models. Kimi K2 (Jul 2025) has 42 scored results on Noometry and MiMo-V2-Omni has 18.