# GLM-4.6V vs MiMo-V2-Pro

> MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 41.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-6v-vs-mimo-v2-pro
- Last updated: 2026-10-12
- Shared benchmarks: 11

## Summary

- They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 1 category and MiMo-V2-Pro in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2-Pro leads 62.8 to 56.6.
- GLM-4.6V is cheaper at $0.30 / $0.90 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2-Pro.
- MiMo-V2-Pro accepts more context: 1.05M tokens versus 128K.
- GLM-4.6V has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-4.6V | MiMo-V2-Pro |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 41.3 | 43.0 |
| Rank | 137 | 103 |
| Context | 128K | 1.05M |
| Input $/M | $0.30 | $0.43 |
| Output $/M | $0.90 | $0.87 |
| Weights | Open | Proprietary |

## Coding

- GLM-4.6V: 40.9 (#128)
- MiMo-V2-Pro: 43.8 (#83)

| Benchmark | GLM-4.6V | MiMo-V2-Pro |
|---|---|---|
| LMArena Coding | 1390 | 1476 |
| LMArena WebDev | — | 1433 |
| ALE-Bench | — | 785.17 |

## Reasoning

- GLM-4.6V: 27.6 (#115)
- MiMo-V2-Pro: 22.1 (#206)

| Benchmark | GLM-4.6V | MiMo-V2-Pro |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1457 |
| NYT Connections (extended) | — | 25.8% |
| Thematic Generalization | — | 45.9% |

## Math

- GLM-4.6V: —
- MiMo-V2-Pro: 39.5 (#102)

| Benchmark | GLM-4.6V | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | — | 1447 |

## Knowledge

- GLM-4.6V: 38.0 (#149)
- MiMo-V2-Pro: 41.4 (#111)

| Benchmark | GLM-4.6V | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1371 | 1478 |

## Multimodal

- GLM-4.6V: 34.8 (#90)
- MiMo-V2-Pro: —

| Benchmark | GLM-4.6V | MiMo-V2-Pro |
|---|---|---|
| LMArena Vision | 1164 | — |

## Multilingual

- GLM-4.6V: 48.6 (#141)
- MiMo-V2-Pro: 52.7 (#81)

| Benchmark | GLM-4.6V | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1359 | 1416 |
| LMArena Chinese | 1425 | 1456 |
| LMArena Russian | 1340 | 1427 |
| LMArena French | — | 1469 |
| LMArena German | — | 1417 |
| LMArena Japanese | — | 1366 |
| LMArena Korean | — | 1400 |
| LMArena Spanish | — | 1457 |

## Instruction Following

- GLM-4.6V: 71.4 (#151)
- MiMo-V2-Pro: 76.0 (#49)

| Benchmark | GLM-4.6V | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1352 | 1445 |

## Long Context

- GLM-4.6V: 41.3 (#143)
- MiMo-V2-Pro: 41.5 (#138)

| Benchmark | GLM-4.6V | MiMo-V2-Pro |
|---|---|---|
| LMArena Longer Query | 1358 | 1455 |
| CL-bench | — | 15.7% |
| CL-bench Life | — | 6.9% |

## Writing & Preference

- GLM-4.6V: 56.6 (#137)
- MiMo-V2-Pro: 62.8 (#70)

| Benchmark | GLM-4.6V | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1377 | 1436 |
| LMArena Creative Writing | 1347 | 1415 |
| LMArena Multi-Turn | 1360 | 1456 |

## FAQ

### Is GLM-4.6V better than MiMo-V2-Pro?

MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 41.3 on the Noometry Index.

### Which is cheaper, GLM-4.6V or MiMo-V2-Pro?

GLM-4.6V is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; MiMo-V2-Pro lists at $0.43 and $0.87.

### Is GLM-4.6V or MiMo-V2-Pro better for coding?

MiMo-V2-Pro scores higher on coding benchmarks: 43.8 versus 40.9 in the Noometry coding category.

### Which has the bigger context window?

MiMo-V2-Pro does, with 1.05M tokens against 128K.

### How many benchmarks do GLM-4.6V and MiMo-V2-Pro share?

11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and MiMo-V2-Pro has 23.