Model comparison
GLM-4.6V vs MiMo-V2-Omni
MiMo-V2-Omni is the stronger model overall, scoring 42.9 to 40.9 on the Noometry Index.
Last verified . 12 shared benchmarks.
Summary
- They share 12 benchmarks with published results for both. GLM-4.6V scores higher in 0 categories and MiMo-V2-Omni in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2-Omni leads 61.6 to 56.8.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.30 / $0.90 for GLM-4.6V.
- MiMo-V2-Omni accepts more context: 262K tokens versus 128K.
- GLM-4.6V has downloadable open weights; the other is API-only.
Side by side
| GLM-4.6V | MiMo-V2-Omni | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 40.9 | 42.9 |
| Released | 2025-12-08 | 2026-03-18 |
| Weights | Open | Proprietary |
| Context window | 128K | 262K |
| Max output | 33K | 131K |
| Input $ / M tokens | $0.30 | $0.14 |
| Output $ / M tokens | $0.90 | $0.28 |
| Results tracked | 12 | 18 |
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Category by category
Coding MiMo-V2-Omni leads
GLM-4.6V: 40.2 (#128), MiMo-V2-Omni: 42.7 (#87)
| Benchmark | GLM-4.6V | MiMo-V2-Omni |
|---|---|---|
| LMArena Coding | 1390 | 1467 |
Reasoning MiMo-V2-Omni leads
GLM-4.6V: 26.5 (#117), MiMo-V2-Omni: 28.6 (#86)
| Benchmark | GLM-4.6V | MiMo-V2-Omni |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1445 |
Math Not comparable
GLM-4.6V: —, MiMo-V2-Omni: 36.4 (#112)
| Benchmark | GLM-4.6V | MiMo-V2-Omni |
|---|---|---|
| LMArena Math | — | 1432 |
Knowledge MiMo-V2-Omni leads
GLM-4.6V: 37.4 (#148), MiMo-V2-Omni: 39.9 (#114)
| Benchmark | GLM-4.6V | MiMo-V2-Omni |
|---|---|---|
| LMArena Expert | 1372 | 1449 |
Multimodal MiMo-V2-Omni leads
GLM-4.6V: 34.2 (#83), MiMo-V2-Omni: 37.9 (#62)
| Benchmark | GLM-4.6V | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | 1164 | 1228 |
Multilingual MiMo-V2-Omni leads
GLM-4.6V: 48.8 (#135), MiMo-V2-Omni: 52.0 (#97)
| Benchmark | GLM-4.6V | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | 1359 | 1404 |
| LMArena Chinese | 1426 | 1469 |
| LMArena Russian | 1341 | 1412 |
| LMArena French | — | 1448 |
| LMArena German | — | 1398 |
| LMArena Japanese | — | 1318 |
| LMArena Korean | — | 1355 |
| LMArena Spanish | — | 1432 |
Instruction Following MiMo-V2-Omni leads
GLM-4.6V: 71.6 (#145), MiMo-V2-Omni: 75.4 (#62)
| Benchmark | GLM-4.6V | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | 1351 | 1428 |
Long Context MiMo-V2-Omni leads
GLM-4.6V: 41.3 (#138), MiMo-V2-Omni: 44.1 (#72)
| Benchmark | GLM-4.6V | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | 1358 | 1442 |
Writing & Preference MiMo-V2-Omni leads
GLM-4.6V: 56.8 (#132), MiMo-V2-Omni: 61.6 (#83)
| Benchmark | GLM-4.6V | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | 1377 | 1424 |
| LMArena Creative Writing | 1347 | 1393 |
| LMArena Multi-Turn | 1359 | 1446 |
Frequently asked questions
Is GLM-4.6V better than MiMo-V2-Omni?
MiMo-V2-Omni is the stronger model overall, scoring 42.9 to 40.9 on the Noometry Index.
Which is cheaper, GLM-4.6V 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-4.6V lists at $0.30 and $0.90.
Is GLM-4.6V or MiMo-V2-Omni better for coding?
MiMo-V2-Omni scores higher on coding benchmarks: 42.7 versus 40.2 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2-Omni does, with 262K tokens against 128K.
How many benchmarks do GLM-4.6V and MiMo-V2-Omni share?
12 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and MiMo-V2-Omni has 18.