Model comparison
GLM-4.5-Air vs MiMo-V2.5-Pro
MiMo-V2.5-Pro is the stronger model overall, scoring 44.8 to 38.7 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-V2.5-Pro in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where MiMo-V2.5-Pro leads 47.0 to 34.5.
- GLM-4.5-Air is cheaper at $0.20 / $1.10 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2.5-Pro.
- MiMo-V2.5-Pro accepts more context: 1.05M tokens versus 131K.
Side by side
| GLM-4.5-Air | MiMo-V2.5-Pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 38.7 | 44.8 |
| Released | 2025-07-20 | 2026-04-22 |
| Weights | Open | Open |
| 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 | 27 |
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Category by category
Coding MiMo-V2.5-Pro leads
GLM-4.5-Air: 34.5 (#225), MiMo-V2.5-Pro: 47.0 (#58)
| Benchmark | GLM-4.5-Air | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Coding | 1397 | 1502 |
| LMArena WebDev | — | 1477 |
| SciCode | — | 50.2% |
| GSO | 2.9% | — |
| ALE-Bench | — | 899.8 |
Reasoning MiMo-V2.5-Pro leads
GLM-4.5-Air: 23.3 (#166), MiMo-V2.5-Pro: 25.9 (#124)
| Benchmark | GLM-4.5-Air | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Hard Prompts | 1379 | 1487 |
| Kagi LLM Benchmark | 43% | — |
| NYT Connections (extended) | — | 34.4% |
| CritPt | — | 4% |
| DTBench | — | 84.5% |
| LMCA | — | 29.5% |
| ForecastBench | 59.2 | — |
Math MiMo-V2.5-Pro leads
GLM-4.5-Air: 33.8 (#166), MiMo-V2.5-Pro: 38.6 (#84)
| Benchmark | GLM-4.5-Air | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Math | 1396 | 1480 |
| ProofBench | — | 22% |
| Omni-MATH | 39.1% | — |
Knowledge MiMo-V2.5-Pro leads
GLM-4.5-Air: 34.6 (#184), MiMo-V2.5-Pro: 41.5 (#100)
| Benchmark | GLM-4.5-Air | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Expert | 1370 | 1501 |
| Humanity's Last Exam | 8.1% | — |
| MMLU-Pro | 76.2% | — |
| Vectara Hallucination Rate | 9.3% | — |
| GPQA (HELM) | 59.4% | — |
Multilingual MiMo-V2.5-Pro leads
GLM-4.5-Air: 49.4 (#130), MiMo-V2.5-Pro: 55.3 (#33)
| Benchmark | GLM-4.5-Air | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Non-English | 1366 | 1449 |
| LMArena Chinese | 1427 | 1507 |
| LMArena French | 1399 | 1489 |
| LMArena German | 1376 | 1455 |
| LMArena Japanese | 1348 | 1418 |
| LMArena Korean | 1306 | 1436 |
| LMArena Russian | 1373 | 1450 |
| LMArena Spanish | 1385 | 1470 |
Instruction Following MiMo-V2.5-Pro leads
GLM-4.5-Air: 69.8 (#165), MiMo-V2.5-Pro: 77.6 (#21)
| Benchmark | GLM-4.5-Air | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Instruction Following | 1353 | 1477 |
| IFEval | 81.2% | — |
Long Context MiMo-V2.5-Pro leads
GLM-4.5-Air: 41.6 (#130), MiMo-V2.5-Pro: 45.4 (#38)
| Benchmark | GLM-4.5-Air | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Longer Query | 1367 | 1482 |
Writing & Preference MiMo-V2.5-Pro leads
GLM-4.5-Air: 56.1 (#134), MiMo-V2.5-Pro: 65.5 (#47)
| Benchmark | GLM-4.5-Air | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Text | 1384 | 1465 |
| LMArena Creative Writing | 1343 | 1440 |
| LMArena Multi-Turn | 1371 | 1477 |
| EQ-Bench Creative Writing | — | 1493 |
| WildBench | 78.9% | — |
| EQ-Bench 4 | — | 1208 |
Frequently asked questions
Is GLM-4.5-Air better than MiMo-V2.5-Pro?
MiMo-V2.5-Pro is the stronger model overall, scoring 44.8 to 38.7 on the Noometry Index.
Which is cheaper, GLM-4.5-Air or MiMo-V2.5-Pro?
GLM-4.5-Air is cheaper. It lists at $0.20 per million input tokens and $1.10 per million output tokens; MiMo-V2.5-Pro lists at $0.43 and $0.87.
Is GLM-4.5-Air or MiMo-V2.5-Pro better for coding?
MiMo-V2.5-Pro scores higher on coding benchmarks: 47.0 versus 34.5 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.5-Pro does, with 1.05M tokens against 131K.
How many benchmarks do GLM-4.5-Air and MiMo-V2.5-Pro share?
17 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and MiMo-V2.5-Pro has 27.