# GLM-5.3-Flash vs MiMo-V2-Omni

> GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 42.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-3-flash-vs-mimo-v2-omni
- Last updated: 2026-10-10
- Shared benchmarks: 18

## Summary

- They share 18 benchmarks with published results for both. GLM-5.3-Flash scores higher in 9 categories and MiMo-V2-Omni in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.3-Flash leads 58.4 to 39.9.
- MiMo-V2-Omni is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.15 / $0.50 for GLM-5.3-Flash.
- GLM-5.3-Flash accepts more context: 1M tokens versus 262K.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-5.3-Flash | MiMo-V2-Omni |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 49.6 | 42.9 |
| Rank | 45 | 91 |
| Context | 1M | 262K |
| Input $/M | $0.15 | $0.14 |
| Output $/M | $0.50 | $0.28 |
| Weights | Open | Proprietary |

## Coding

- GLM-5.3-Flash: 53.7 (#26)
- MiMo-V2-Omni: 42.7 (#87)

| Benchmark | GLM-5.3-Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Coding | 1506 | 1467 |
| DeepSWE | 63.4% | — |
| FrontierCode | 31.8% | — |
| LMArena WebDev | 1614 | — |
| SciCode | 51.6% | — |
| ALE-Bench | 303.55 | — |

## Agentic & Tool Use

- GLM-5.3-Flash: 34.3 (#41)
- MiMo-V2-Omni: —

| Benchmark | GLM-5.3-Flash | MiMo-V2-Omni |
|---|---|---|
| APEX-Agents | 52.8% | — |
| GDP.pdf | 14% | — |

## Reasoning

- GLM-5.3-Flash: 31.7 (#69)
- MiMo-V2-Omni: 28.6 (#86)

| Benchmark | GLM-5.3-Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Hard Prompts | 1490 | 1445 |
| CritPt | 15.4% | — |
| Chess Puzzles | 14% | — |
| Mystery Game Puzzles | 8% | — |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |
| Epoch Capabilities Index | 151.9 | — |

## Math

- GLM-5.3-Flash: 53.1 (#38)
- MiMo-V2-Omni: 36.4 (#112)

| Benchmark | GLM-5.3-Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Math | 1499 | 1432 |
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 17.1% | — |
| OTIS Mock AIME 2024-2025 | 93.9% | — |
| ProofBench | 21% | — |

## Knowledge

- GLM-5.3-Flash: 58.4 (#33)
- MiMo-V2-Omni: 39.9 (#114)

| Benchmark | GLM-5.3-Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Expert | 1512 | 1449 |
| GPQA Diamond | 90.2% | — |

## Multimodal

- GLM-5.3-Flash: 42.6 (#25)
- MiMo-V2-Omni: 37.9 (#62)

| Benchmark | GLM-5.3-Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | 1304 | 1228 |

## Multilingual

- GLM-5.3-Flash: 56.2 (#24)
- MiMo-V2-Omni: 52.0 (#97)

| Benchmark | GLM-5.3-Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | 1462 | 1404 |
| LMArena Chinese | 1529 | 1469 |
| LMArena French | 1495 | 1448 |
| LMArena German | 1457 | 1398 |
| LMArena Japanese | 1420 | 1318 |
| LMArena Korean | 1443 | 1355 |
| LMArena Russian | 1472 | 1412 |
| LMArena Spanish | 1471 | 1432 |

## Instruction Following

- GLM-5.3-Flash: 77.8 (#17)
- MiMo-V2-Omni: 75.4 (#62)

| Benchmark | GLM-5.3-Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | 1480 | 1428 |

## Long Context

- GLM-5.3-Flash: 45.3 (#41)
- MiMo-V2-Omni: 44.1 (#72)

| Benchmark | GLM-5.3-Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | 1479 | 1442 |

## Writing & Preference

- GLM-5.3-Flash: 65.4 (#49)
- MiMo-V2-Omni: 61.6 (#83)

| Benchmark | GLM-5.3-Flash | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | 1471 | 1424 |
| LMArena Creative Writing | 1440 | 1393 |
| LMArena Multi-Turn | 1471 | 1446 |

## FAQ

### Is GLM-5.3-Flash better than MiMo-V2-Omni?

GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 42.9 on the Noometry Index.

### Which is cheaper, GLM-5.3-Flash 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-5.3-Flash lists at $0.15 and $0.50.

### Is GLM-5.3-Flash or MiMo-V2-Omni better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.7 versus 42.7 in the Noometry coding category.

### Which has the bigger context window?

GLM-5.3-Flash does, with 1M tokens against 262K.

### How many benchmarks do GLM-5.3-Flash and MiMo-V2-Omni share?

18 benchmarks have published results for both models. GLM-5.3-Flash has 36 scored results on Noometry and MiMo-V2-Omni has 18.