Model comparison
GLM-4.5-Air vs MiMo-V2-Pro
MiMo-V2-Pro is the stronger model overall, scoring 43.0 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 2 categories and MiMo-V2-Pro in 6 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in coding, where MiMo-V2-Pro leads 43.8 to 33.3.
- GLM-4.5-Air is cheaper at $0.20 / $1.10 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2-Pro.
- MiMo-V2-Pro accepts more context: 1.05M 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-Pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 38.9 | 43.0 |
| Released | 2025-07-20 | 2026-03-18 |
| Weights | Open | Proprietary |
| Context window | 131K | 1.05M |
| Max output | 98K | 131K |
| Input $ / M tokens | $0.20 | $0.43 |
| Output $ / M tokens | $1.10 | $0.87 |
| Results tracked | 27 | 23 |
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Category by category
Coding MiMo-V2-Pro leads
GLM-4.5-Air: 33.3 (#259), MiMo-V2-Pro: 43.8 (#83)
| Benchmark | GLM-4.5-Air | MiMo-V2-Pro |
|---|---|---|
| LMArena Coding | 1397 | 1476 |
| LMArena WebDev | — | 1433 |
| GSO | 2.9% | — |
| ALE-Bench | — | 785.17 |
Reasoning GLM-4.5-Air leads
GLM-4.5-Air: 24.1 (#166), MiMo-V2-Pro: 22.1 (#206)
| Benchmark | GLM-4.5-Air | MiMo-V2-Pro |
|---|---|---|
| LMArena Hard Prompts | 1379 | 1457 |
| Kagi LLM Benchmark | 43% | — |
| NYT Connections (extended) | — | 25.8% |
| Thematic Generalization | — | 45.9% |
| ForecastBench | 59.2 | — |
Math MiMo-V2-Pro leads
GLM-4.5-Air: 36.2 (#170), MiMo-V2-Pro: 39.5 (#102)
| Benchmark | GLM-4.5-Air | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | 1396 | 1447 |
| Omni-MATH | 39.1% | — |
Knowledge MiMo-V2-Pro leads
GLM-4.5-Air: 35.0 (#191), MiMo-V2-Pro: 41.4 (#111)
| Benchmark | GLM-4.5-Air | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1370 | 1478 |
| Humanity's Last Exam | 8.1% | — |
| MMLU-Pro | 76.2% | — |
| Vectara Hallucination Rate | 9.3% | — |
| GPQA (HELM) | 59.4% | — |
Multilingual MiMo-V2-Pro leads
GLM-4.5-Air: 49.1 (#135), MiMo-V2-Pro: 52.7 (#81)
| Benchmark | GLM-4.5-Air | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1366 | 1416 |
| LMArena Chinese | 1426 | 1456 |
| LMArena French | 1399 | 1469 |
| LMArena German | 1377 | 1417 |
| LMArena Japanese | 1348 | 1366 |
| LMArena Korean | 1308 | 1400 |
| LMArena Russian | 1373 | 1427 |
| LMArena Spanish | 1386 | 1457 |
Instruction Following MiMo-V2-Pro leads
GLM-4.5-Air: 69.6 (#171), MiMo-V2-Pro: 76.0 (#49)
| Benchmark | GLM-4.5-Air | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1354 | 1445 |
| IFEval | 81.2% | — |
Long Context Too close to call
GLM-4.5-Air: 41.6 (#135), MiMo-V2-Pro: 41.5 (#138)
| Benchmark | GLM-4.5-Air | MiMo-V2-Pro |
|---|---|---|
| LMArena Longer Query | 1366 | 1455 |
| CL-bench | — | 15.7% |
| CL-bench Life | — | 6.9% |
Writing & Preference MiMo-V2-Pro leads
GLM-4.5-Air: 55.9 (#139), MiMo-V2-Pro: 62.8 (#70)
| Benchmark | GLM-4.5-Air | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1384 | 1436 |
| LMArena Creative Writing | 1343 | 1415 |
| LMArena Multi-Turn | 1371 | 1456 |
| WildBench | 78.9% | — |
Frequently asked questions
Is GLM-4.5-Air better than MiMo-V2-Pro?
MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 38.9 on the Noometry Index.
Which is cheaper, GLM-4.5-Air or MiMo-V2-Pro?
GLM-4.5-Air is cheaper. It lists at $0.20 per million input tokens and $1.10 per million output tokens; MiMo-V2-Pro lists at $0.43 and $0.87.
Is GLM-4.5-Air or MiMo-V2-Pro better for coding?
MiMo-V2-Pro scores higher on coding benchmarks: 43.8 versus 33.3 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2-Pro does, with 1.05M tokens against 131K.
How many benchmarks do GLM-4.5-Air and MiMo-V2-Pro share?
17 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and MiMo-V2-Pro has 23.