# GLM-4.6 vs MiMo-V2-Pro

> MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 41.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-6-vs-mimo-v2-pro
- Last updated: 2026-10-10
- Shared benchmarks: 19

## Summary

- They share 19 benchmarks with published results for both. GLM-4.6 scores higher in 3 categories and MiMo-V2-Pro in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in coding, where MiMo-V2-Pro leads 43.8 to 40.1.
- MiMo-V2-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.
- MiMo-V2-Pro accepts more context: 1.05M tokens versus 205K.
- GLM-4.6 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-4.6 | MiMo-V2-Pro |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 41.4 | 43.0 |
| Rank | 135 | 103 |
| Context | 205K | 1.05M |
| Input $/M | $0.60 | $0.43 |
| Output $/M | $2.20 | $0.87 |
| Weights | Open | Proprietary |

## Coding

- GLM-4.6: 40.1 (#148)
- MiMo-V2-Pro: 43.8 (#83)

| Benchmark | GLM-4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena WebDev | 1340 | 1433 |
| LMArena Coding | 1449 | 1476 |
| ALE-Bench | 340.82 | 785.17 |
| SWE-bench Verified (bash only) | 55.4% | — |
| SciCode | 38.4% | — |

## Agentic & Tool Use

- GLM-4.6: 32.3 (#66)
- MiMo-V2-Pro: —

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

## Reasoning

- GLM-4.6: 23.7 (#172)
- MiMo-V2-Pro: 22.1 (#206)

| Benchmark | GLM-4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Hard Prompts | 1440 | 1457 |
| Kagi LLM Benchmark | 47.4% | — |
| NYT Connections (extended) | — | 25.8% |
| CritPt | 1.1% | — |
| Thematic Generalization | — | 45.9% |

## Math

- GLM-4.6: 39.1 (#111)
- MiMo-V2-Pro: 39.5 (#102)

| Benchmark | GLM-4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | 1432 | 1447 |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-4.6: 40.2 (#124)
- MiMo-V2-Pro: 41.4 (#111)

| Benchmark | GLM-4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1431 | 1478 |
| Vectara Hallucination Rate | 9.5% | — |

## Multilingual

- GLM-4.6: 53.5 (#66)
- MiMo-V2-Pro: 52.7 (#81)

| Benchmark | GLM-4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1426 | 1416 |
| LMArena Chinese | 1499 | 1456 |
| LMArena French | 1459 | 1469 |
| LMArena German | 1447 | 1417 |
| LMArena Japanese | 1393 | 1366 |
| LMArena Korean | 1400 | 1400 |
| LMArena Russian | 1419 | 1427 |
| LMArena Spanish | 1436 | 1457 |

## Instruction Following

- GLM-4.6: 74.3 (#98)
- MiMo-V2-Pro: 76.0 (#49)

| Benchmark | GLM-4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1410 | 1445 |

## Long Context

- GLM-4.6: 43.4 (#94)
- MiMo-V2-Pro: 41.5 (#138)

| Benchmark | GLM-4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Longer Query | 1422 | 1455 |
| CL-bench | — | 15.7% |
| CL-bench Life | — | 6.9% |

## Writing & Preference

- GLM-4.6: 61.1 (#90)
- MiMo-V2-Pro: 62.8 (#70)

| Benchmark | GLM-4.6 | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1440 | 1436 |
| LMArena Creative Writing | 1411 | 1415 |
| LMArena Multi-Turn | 1427 | 1456 |
| EQ-Bench Creative Writing | 1411 | — |

## FAQ

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

MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 41.4 on the Noometry Index.

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

MiMo-V2-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

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

MiMo-V2-Pro scores higher on coding benchmarks: 43.8 versus 40.1 in the Noometry coding category.

### Which has the bigger context window?

MiMo-V2-Pro does, with 1.05M tokens against 205K.

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

19 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and MiMo-V2-Pro has 23.