# GLM-4.6 vs MiMo-V2-Omni

> MiMo-V2-Omni is the stronger model overall, scoring 42.9 to 40.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-6-vs-mimo-v2-omni
- Last updated: 2026-10-10
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. GLM-4.6 scores higher in 1 category and MiMo-V2-Omni in 7 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where MiMo-V2-Omni leads 28.6 to 23.1.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.
- MiMo-V2-Omni accepts more context: 262K tokens versus 205K.
- GLM-4.6 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-4.6 | MiMo-V2-Omni |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 40.9 | 42.9 |
| Rank | 132 | 91 |
| Context | 205K | 262K |
| Input $/M | $0.60 | $0.14 |
| Output $/M | $2.20 | $0.28 |
| Weights | Open | Proprietary |

## Coding

- GLM-4.6: 39.9 (#137)
- MiMo-V2-Omni: 42.7 (#87)

| Benchmark | GLM-4.6 | MiMo-V2-Omni |
|---|---|---|
| LMArena Coding | 1449 | 1467 |
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1339 | — |
| SciCode | 38.4% | — |
| ALE-Bench | 340.82 | — |

## Agentic & Tool Use

- GLM-4.6: 32.1 (#60)
- MiMo-V2-Omni: —

| Benchmark | GLM-4.6 | MiMo-V2-Omni |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |

## Reasoning

- GLM-4.6: 23.1 (#168)
- MiMo-V2-Omni: 28.6 (#86)

| Benchmark | GLM-4.6 | MiMo-V2-Omni |
|---|---|---|
| LMArena Hard Prompts | 1440 | 1445 |
| Kagi LLM Benchmark | 47.4% | — |
| CritPt | 1.1% | — |

## Math

- GLM-4.6: 36.4 (#115)
- MiMo-V2-Omni: 36.4 (#112)

| Benchmark | GLM-4.6 | MiMo-V2-Omni |
|---|---|---|
| LMArena Math | 1431 | 1432 |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-4.6: 39.6 (#118)
- MiMo-V2-Omni: 39.9 (#114)

| Benchmark | GLM-4.6 | MiMo-V2-Omni |
|---|---|---|
| LMArena Expert | 1432 | 1449 |
| Vectara Hallucination Rate | 9.5% | — |

## Multimodal

- GLM-4.6: —
- MiMo-V2-Omni: 37.9 (#62)

| Benchmark | GLM-4.6 | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | — | 1228 |

## Multilingual

- GLM-4.6: 53.6 (#62)
- MiMo-V2-Omni: 52.0 (#97)

| Benchmark | GLM-4.6 | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | 1426 | 1404 |
| LMArena Chinese | 1500 | 1469 |
| LMArena French | 1459 | 1448 |
| LMArena German | 1447 | 1398 |
| LMArena Japanese | 1394 | 1318 |
| LMArena Korean | 1401 | 1355 |
| LMArena Russian | 1418 | 1412 |
| LMArena Spanish | 1436 | 1432 |

## Instruction Following

- GLM-4.6: 74.5 (#93)
- MiMo-V2-Omni: 75.4 (#62)

| Benchmark | GLM-4.6 | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | 1410 | 1428 |

## Long Context

- GLM-4.6: 43.4 (#91)
- MiMo-V2-Omni: 44.1 (#72)

| Benchmark | GLM-4.6 | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | 1423 | 1442 |

## Writing & Preference

- GLM-4.6: 61.3 (#86)
- MiMo-V2-Omni: 61.6 (#83)

| Benchmark | GLM-4.6 | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | 1440 | 1424 |
| LMArena Creative Writing | 1411 | 1393 |
| LMArena Multi-Turn | 1427 | 1446 |
| EQ-Bench Creative Writing | 1411 | — |

## FAQ

### Is GLM-4.6 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-4.6 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-4.6 lists at $0.60 and $2.20.

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

MiMo-V2-Omni scores higher on coding benchmarks: 42.7 versus 39.9 in the Noometry coding category.

### Which has the bigger context window?

MiMo-V2-Omni does, with 262K tokens against 205K.

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

17 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and MiMo-V2-Omni has 18.