Model comparison
GLM-4.5-Air vs MiMo-V2-Omni
MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 38.9 on the Noometry Index.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. GLM-4.5-Air scores higher in 0 categories and MiMo-V2-Omni in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where MiMo-V2-Omni leads 43.3 to 33.3.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.20 / $1.10 for GLM-4.5-Air.
- MiMo-V2-Omni accepts more context: 262K tokens versus 131K.
- GLM-4.5-Air has downloadable open weights; the other is API-only.
Side by side
| GLM-4.5-Air | MiMo-V2-Omni | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 38.9 | 43.6 |
| Released | 2025-07-20 | 2026-03-18 |
| Weights | Open | Proprietary |
| Context window | 131K | 262K |
| Max output | 98K | 131K |
| Input $ / M tokens | $0.20 | $0.14 |
| Output $ / M tokens | $1.10 | $0.28 |
| Results tracked | 27 | 18 |
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Category by category
Coding MiMo-V2-Omni leads
GLM-4.5-Air: 33.3 (#259), MiMo-V2-Omni: 43.3 (#89)
| Benchmark | GLM-4.5-Air | MiMo-V2-Omni |
|---|---|---|
| LMArena Coding | 1397 | 1466 |
| GSO | 2.9% | — |
Reasoning MiMo-V2-Omni leads
GLM-4.5-Air: 24.1 (#166), MiMo-V2-Omni: 29.7 (#88)
| Benchmark | GLM-4.5-Air | MiMo-V2-Omni |
|---|---|---|
| LMArena Hard Prompts | 1379 | 1445 |
| Kagi LLM Benchmark | 43% | — |
| ForecastBench | 59.2 | — |
Math MiMo-V2-Omni leads
GLM-4.5-Air: 36.2 (#170), MiMo-V2-Omni: 39.1 (#115)
| Benchmark | GLM-4.5-Air | MiMo-V2-Omni |
|---|---|---|
| LMArena Math | 1396 | 1430 |
| Omni-MATH | 39.1% | — |
Knowledge MiMo-V2-Omni leads
GLM-4.5-Air: 35.0 (#191), MiMo-V2-Omni: 40.5 (#118)
| Benchmark | GLM-4.5-Air | MiMo-V2-Omni |
|---|---|---|
| LMArena Expert | 1370 | 1449 |
| Humanity's Last Exam | 8.1% | — |
| MMLU-Pro | 76.2% | — |
| Vectara Hallucination Rate | 9.3% | — |
| GPQA (HELM) | 59.4% | — |
Multimodal Not comparable
GLM-4.5-Air: —, MiMo-V2-Omni: 38.6 (#63)
| Benchmark | GLM-4.5-Air | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | — | 1228 |
Multilingual MiMo-V2-Omni leads
GLM-4.5-Air: 49.1 (#135), MiMo-V2-Omni: 51.8 (#102)
| Benchmark | GLM-4.5-Air | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | 1366 | 1404 |
| LMArena Chinese | 1426 | 1465 |
| LMArena French | 1399 | 1447 |
| LMArena German | 1377 | 1399 |
| LMArena Japanese | 1348 | 1317 |
| LMArena Korean | 1308 | 1355 |
| LMArena Russian | 1373 | 1412 |
| LMArena Spanish | 1386 | 1434 |
Instruction Following MiMo-V2-Omni leads
GLM-4.5-Air: 69.6 (#171), MiMo-V2-Omni: 75.2 (#66)
| Benchmark | GLM-4.5-Air | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | 1354 | 1428 |
| IFEval | 81.2% | — |
Long Context MiMo-V2-Omni leads
GLM-4.5-Air: 41.6 (#135), MiMo-V2-Omni: 44.1 (#76)
| Benchmark | GLM-4.5-Air | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | 1366 | 1442 |
Writing & Preference MiMo-V2-Omni leads
GLM-4.5-Air: 55.9 (#139), MiMo-V2-Omni: 61.4 (#87)
| Benchmark | GLM-4.5-Air | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | 1384 | 1423 |
| LMArena Creative Writing | 1343 | 1392 |
| LMArena Multi-Turn | 1371 | 1445 |
| WildBench | 78.9% | — |
Frequently asked questions
Is GLM-4.5-Air better than MiMo-V2-Omni?
MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 38.9 on the Noometry Index.
Which is cheaper, GLM-4.5-Air 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; GLM-4.5-Air lists at $0.20 and $1.10.
Is GLM-4.5-Air or MiMo-V2-Omni better for coding?
MiMo-V2-Omni scores higher on coding benchmarks: 43.3 versus 33.3 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2-Omni does, with 262K tokens against 131K.
How many benchmarks do GLM-4.5-Air and MiMo-V2-Omni share?
17 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and MiMo-V2-Omni has 18.