# GLM-4.6 vs Pixtral Large

> GLM-4.6 is the stronger model overall, scoring 41.4 to 32.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-6-vs-pixtral-large
- Last updated: 2026-10-11
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. GLM-4.6 scores higher in 2 categories and Pixtral Large in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.6 leads 61.1 to 32.9.
- GLM-4.6 is cheaper at $0.60 / $2.20 per million input/output tokens, against $2 / $6 for Pixtral Large.
- GLM-4.6 accepts more context: 205K tokens versus 128K.

## Snapshot

| | GLM-4.6 | Pixtral Large |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 41.4 | 32.2 |
| Rank | 135 | 259 |
| Context | 205K | 128K |
| Input $/M | $0.60 | $2 |
| Output $/M | $2.20 | $6 |
| Weights | Open | Open |

## Coding

- GLM-4.6: 40.1 (#148)
- Pixtral Large: —

| Benchmark | GLM-4.6 | Pixtral Large |
|---|---|---|
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1340 | — |
| SciCode | 38.4% | — |
| LMArena Coding | 1449 | — |
| ALE-Bench | 340.82 | — |

## Agentic & Tool Use

- GLM-4.6: 32.3 (#66)
- Pixtral Large: —

| Benchmark | GLM-4.6 | Pixtral Large |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |

## Reasoning

- GLM-4.6: 23.7 (#172)
- Pixtral Large: 21.7 (#218)

| Benchmark | GLM-4.6 | Pixtral Large |
|---|---|---|
| Kagi LLM Benchmark | 47.4% | — |
| CritPt | 1.1% | — |
| EnigmaEval | — | 0.8% |
| LMArena Hard Prompts | 1440 | — |

## Math

- GLM-4.6: 39.1 (#111)
- Pixtral Large: —

| Benchmark | GLM-4.6 | Pixtral Large |
|---|---|---|
| LMArena Math | 1432 | — |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-4.6: 40.2 (#124)
- Pixtral Large: —

| Benchmark | GLM-4.6 | Pixtral Large |
|---|---|---|
| Vectara Hallucination Rate | 9.5% | — |
| LMArena Expert | 1431 | — |

## Multimodal

- GLM-4.6: —
- Pixtral Large: 30.6 (#111)

| Benchmark | GLM-4.6 | Pixtral Large |
|---|---|---|
| LMArena Vision | — | 1089 |

## Multilingual

- GLM-4.6: 53.5 (#66)
- Pixtral Large: —

| Benchmark | GLM-4.6 | Pixtral Large |
|---|---|---|
| LMArena Non-English | 1426 | — |
| LMArena Chinese | 1499 | — |
| LMArena French | 1459 | — |
| LMArena German | 1447 | — |
| LMArena Japanese | 1393 | — |
| LMArena Korean | 1400 | — |
| LMArena Russian | 1419 | — |
| LMArena Spanish | 1436 | — |

## Instruction Following

- GLM-4.6: 74.3 (#98)
- Pixtral Large: —

| Benchmark | GLM-4.6 | Pixtral Large |
|---|---|---|
| LMArena Instruction Following | 1410 | — |

## Long Context

- GLM-4.6: 43.4 (#94)
- Pixtral Large: —

| Benchmark | GLM-4.6 | Pixtral Large |
|---|---|---|
| LMArena Longer Query | 1422 | — |

## Writing & Preference

- GLM-4.6: 61.1 (#90)
- Pixtral Large: 32.9 (#278)

| Benchmark | GLM-4.6 | Pixtral Large |
|---|---|---|
| EQ-Bench Creative Writing | 1411 | 988 |
| LMArena Text | 1440 | — |
| LMArena Creative Writing | 1411 | — |
| LMArena Multi-Turn | 1427 | — |

## FAQ

### Is GLM-4.6 better than Pixtral Large?

GLM-4.6 is the stronger model overall, scoring 41.4 to 32.2 on the Noometry Index.

### Which is cheaper, GLM-4.6 or Pixtral Large?

GLM-4.6 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Pixtral Large lists at $2 and $6.

### Which has the bigger context window?

GLM-4.6 does, with 205K tokens against 128K.

### How many benchmarks do GLM-4.6 and Pixtral Large share?

1 benchmark has published results for both models. GLM-4.6 has 29 scored results on Noometry and Pixtral Large has 3.