Model comparison
GLM-4.5 vs MiMo-V2-Pro
GLM-4.5 and MiMo-V2-Pro score almost the same on the Noometry Index (42.0 vs 43.0), so choose on price, context window or the category you care about most.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. GLM-4.5 scores higher in 2 categories and MiMo-V2-Pro in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.5 leads 28.6 to 22.1.
- MiMo-V2-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.
- MiMo-V2-Pro accepts more context: 1.05M tokens versus 131K.
- GLM-4.5 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.5 | MiMo-V2-Pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 42.0 | 43.0 |
| Released | 2025-07-27 | 2026-03-18 |
| Weights | Open | Proprietary |
| Context window | 131K | 1.05M |
| Max output | 98K | 131K |
| Input $ / M tokens | $0.60 | $0.43 |
| Output $ / M tokens | $2.20 | $0.87 |
| Results tracked | 27 | 23 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding MiMo-V2-Pro leads
GLM-4.5: 41.4 (#125), MiMo-V2-Pro: 43.8 (#83)
| Benchmark | GLM-4.5 | MiMo-V2-Pro |
|---|---|---|
| LMArena Coding | 1434 | 1476 |
| ALE-Bench | 344.82 | 785.17 |
| SWE-bench Verified (bash only) | 54.2% | — |
| LMArena WebDev | — | 1433 |
| WeirdML | 40.6% | — |
| AlgoTune | 1.52 | — |
Reasoning GLM-4.5 leads
GLM-4.5: 28.6 (#100), MiMo-V2-Pro: 22.1 (#206)
| Benchmark | GLM-4.5 | MiMo-V2-Pro |
|---|---|---|
| LMArena Hard Prompts | 1429 | 1457 |
| Kagi LLM Benchmark | 57.9% | — |
| NYT Connections (extended) | — | 25.8% |
| Thematic Generalization | — | 45.9% |
Math Too close to call
GLM-4.5: 39.0 (#116), MiMo-V2-Pro: 39.5 (#102)
| Benchmark | GLM-4.5 | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | 1427 | 1447 |
Knowledge MiMo-V2-Pro leads
GLM-4.5: 35.9 (#179), MiMo-V2-Pro: 41.4 (#111)
| Benchmark | GLM-4.5 | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1433 | 1478 |
| Humanity's Last Exam | 8.3% | — |
| Confabulations | 11.3% | — |
Multilingual Too close to call
GLM-4.5: 52.8 (#77), MiMo-V2-Pro: 52.7 (#81)
| Benchmark | GLM-4.5 | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1417 | 1416 |
| LMArena Chinese | 1465 | 1456 |
| LMArena French | 1418 | 1469 |
| LMArena German | 1407 | 1417 |
| LMArena Japanese | 1415 | 1366 |
| LMArena Korean | 1380 | 1400 |
| LMArena Russian | 1414 | 1427 |
| LMArena Spanish | 1454 | 1457 |
Instruction Following MiMo-V2-Pro leads
GLM-4.5: 74.1 (#104), MiMo-V2-Pro: 76.0 (#49)
| Benchmark | GLM-4.5 | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1404 | 1445 |
Long Context MiMo-V2-Pro leads
GLM-4.5: 38.2 (#201), MiMo-V2-Pro: 41.5 (#138)
| Benchmark | GLM-4.5 | MiMo-V2-Pro |
|---|---|---|
| LMArena Longer Query | 1412 | 1455 |
| Fiction.LiveBench | 58.3% | — |
| CL-bench | — | 15.7% |
| CL-bench Life | — | 6.9% |
Writing & Preference MiMo-V2-Pro leads
GLM-4.5: 57.5 (#127), MiMo-V2-Pro: 62.8 (#70)
| Benchmark | GLM-4.5 | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1430 | 1436 |
| LMArena Creative Writing | 1395 | 1415 |
| LMArena Multi-Turn | 1415 | 1456 |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
Frequently asked questions
Is GLM-4.5 better than MiMo-V2-Pro?
GLM-4.5 and MiMo-V2-Pro score almost the same on the Noometry Index (42.0 vs 43.0), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-4.5 or MiMo-V2-Pro?
MiMo-V2-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.
Is GLM-4.5 or MiMo-V2-Pro better for coding?
MiMo-V2-Pro scores higher on coding benchmarks: 43.8 versus 41.4 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 and MiMo-V2-Pro share?
18 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and MiMo-V2-Pro has 23.