Model comparison
GLM-4.5 vs MiMo-V2-Omni
MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 42.0 on the Noometry Index.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. GLM-4.5 scores higher in 1 category and MiMo-V2-Omni in 7 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in long context, where MiMo-V2-Omni leads 44.1 to 38.2.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.
- MiMo-V2-Omni accepts more context: 262K tokens versus 131K.
- GLM-4.5 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.5 | MiMo-V2-Omni | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 42.0 | 43.6 |
| Released | 2025-07-27 | 2026-03-18 |
| Weights | Open | Proprietary |
| Context window | 131K | 262K |
| Max output | 98K | 131K |
| Input $ / M tokens | $0.60 | $0.14 |
| Output $ / M tokens | $2.20 | $0.28 |
| Results tracked | 27 | 18 |
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Category by category
Coding MiMo-V2-Omni leads
GLM-4.5: 41.4 (#125), MiMo-V2-Omni: 43.3 (#89)
| Benchmark | GLM-4.5 | MiMo-V2-Omni |
|---|---|---|
| LMArena Coding | 1434 | 1466 |
| SWE-bench Verified (bash only) | 54.2% | — |
| WeirdML | 40.6% | — |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |
Reasoning MiMo-V2-Omni leads
GLM-4.5: 28.6 (#100), MiMo-V2-Omni: 29.7 (#88)
| Benchmark | GLM-4.5 | MiMo-V2-Omni |
|---|---|---|
| LMArena Hard Prompts | 1429 | 1445 |
| Kagi LLM Benchmark | 57.9% | — |
Math Too close to call
GLM-4.5: 39.0 (#116), MiMo-V2-Omni: 39.1 (#115)
| Benchmark | GLM-4.5 | MiMo-V2-Omni |
|---|---|---|
| LMArena Math | 1427 | 1430 |
Knowledge MiMo-V2-Omni leads
GLM-4.5: 35.9 (#179), MiMo-V2-Omni: 40.5 (#118)
| Benchmark | GLM-4.5 | MiMo-V2-Omni |
|---|---|---|
| LMArena Expert | 1433 | 1449 |
| Humanity's Last Exam | 8.3% | — |
| Confabulations | 11.3% | — |
Multimodal Not comparable
GLM-4.5: —, MiMo-V2-Omni: 38.6 (#63)
| Benchmark | GLM-4.5 | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | — | 1228 |
Multilingual Too close to call
GLM-4.5: 52.8 (#77), MiMo-V2-Omni: 51.8 (#102)
| Benchmark | GLM-4.5 | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | 1417 | 1404 |
| LMArena Chinese | 1465 | 1465 |
| LMArena French | 1418 | 1447 |
| LMArena German | 1407 | 1399 |
| LMArena Japanese | 1415 | 1317 |
| LMArena Korean | 1380 | 1355 |
| LMArena Russian | 1414 | 1412 |
| LMArena Spanish | 1454 | 1434 |
Instruction Following MiMo-V2-Omni leads
GLM-4.5: 74.1 (#104), MiMo-V2-Omni: 75.2 (#66)
| Benchmark | GLM-4.5 | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | 1404 | 1428 |
Long Context MiMo-V2-Omni leads
GLM-4.5: 38.2 (#201), MiMo-V2-Omni: 44.1 (#76)
| Benchmark | GLM-4.5 | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | 1412 | 1442 |
| Fiction.LiveBench | 58.3% | — |
Writing & Preference MiMo-V2-Omni leads
GLM-4.5: 57.5 (#127), MiMo-V2-Omni: 61.4 (#87)
| Benchmark | GLM-4.5 | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | 1430 | 1423 |
| LMArena Creative Writing | 1395 | 1392 |
| LMArena Multi-Turn | 1415 | 1445 |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
Frequently asked questions
Is GLM-4.5 better than MiMo-V2-Omni?
MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 42.0 on the Noometry Index.
Which is cheaper, GLM-4.5 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 lists at $0.60 and $2.20.
Is GLM-4.5 or MiMo-V2-Omni better for coding?
MiMo-V2-Omni scores higher on coding benchmarks: 43.3 versus 41.4 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 and MiMo-V2-Omni share?
17 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and MiMo-V2-Omni has 18.