# GLM-4.6V vs Mistral Large 3

> GLM-4.6V is the stronger model overall, scoring 40.9 to 38.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-6v-vs-mistral-large-3
- Last updated: 2026-10-10
- Shared benchmarks: 12

## Summary

- They share 12 benchmarks with published results for both. GLM-4.6V scores higher in 3 categories and Mistral Large 3 in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.6V leads 26.5 to 14.6.
- Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $0.30 / $0.90 for GLM-4.6V.
- Mistral Large 3 accepts more context: 262K tokens versus 128K.

## Snapshot

| | GLM-4.6V | Mistral Large 3 |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 40.9 | 38.6 |
| Rank | 133 | 172 |
| Context | 128K | 262K |
| Input $/M | $0.30 | $0.25 |
| Output $/M | $0.90 | $0.75 |
| Weights | Open | Open |

## Coding

- GLM-4.6V: 40.2 (#128)
- Mistral Large 3: 34.1 (#230)

| Benchmark | GLM-4.6V | Mistral Large 3 |
|---|---|---|
| LMArena Coding | 1390 | 1447 |
| LMArena WebDev | — | 1230 |

## Reasoning

- GLM-4.6V: 26.5 (#117)
- Mistral Large 3: 14.6 (#314)

| Benchmark | GLM-4.6V | Mistral Large 3 |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1429 |
| Kagi LLM Benchmark | — | 50.9% |
| NYT Connections (extended) | — | 7.5% |
| Thematic Generalization | — | 23% |

## Math

- GLM-4.6V: —
- Mistral Large 3: 36.0 (#131)

| Benchmark | GLM-4.6V | Mistral Large 3 |
|---|---|---|
| LMArena Math | — | 1415 |

## Knowledge

- GLM-4.6V: 37.4 (#148)
- Mistral Large 3: 35.5 (#173)

| Benchmark | GLM-4.6V | Mistral Large 3 |
|---|---|---|
| LMArena Expert | 1372 | 1421 |
| Vectara Hallucination Rate | — | 14.5% |

## Multimodal

- GLM-4.6V: 34.2 (#83)
- Mistral Large 3: 37.6 (#65)

| Benchmark | GLM-4.6V | Mistral Large 3 |
|---|---|---|
| LMArena Vision | 1164 | 1222 |

## Multilingual

- GLM-4.6V: 48.8 (#135)
- Mistral Large 3: 52.6 (#79)

| Benchmark | GLM-4.6V | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1359 | 1412 |
| LMArena Chinese | 1426 | 1448 |
| LMArena Russian | 1341 | 1412 |
| LMArena French | — | 1456 |
| LMArena German | — | 1438 |
| LMArena Japanese | — | 1399 |
| LMArena Korean | — | 1384 |
| LMArena Spanish | — | 1437 |

## Instruction Following

- GLM-4.6V: 71.6 (#145)
- Mistral Large 3: 74.1 (#104)

| Benchmark | GLM-4.6V | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1351 | 1402 |

## Long Context

- GLM-4.6V: 41.3 (#138)
- Mistral Large 3: 43.1 (#102)

| Benchmark | GLM-4.6V | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1358 | 1413 |

## Writing & Preference

- GLM-4.6V: 56.8 (#132)
- Mistral Large 3: 60.2 (#100)

| Benchmark | GLM-4.6V | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1377 | 1427 |
| LMArena Creative Writing | 1347 | 1385 |
| LMArena Multi-Turn | 1359 | 1429 |
| EQ-Bench Creative Writing | — | 1412 |

## FAQ

### Is GLM-4.6V better than Mistral Large 3?

GLM-4.6V is the stronger model overall, scoring 40.9 to 38.6 on the Noometry Index.

### Which is cheaper, GLM-4.6V or Mistral Large 3?

Mistral Large 3 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; GLM-4.6V lists at $0.30 and $0.90.

### Is GLM-4.6V or Mistral Large 3 better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.2 versus 34.1 in the Noometry coding category.

### Which has the bigger context window?

Mistral Large 3 does, with 262K tokens against 128K.

### How many benchmarks do GLM-4.6V and Mistral Large 3 share?

12 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Mistral Large 3 has 24.