# GLM-4.6 vs Mistral Medium

> GLM-4.6 is the stronger model overall, scoring 40.9 to 36.0 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-6-vs-mistral-medium
- Last updated: 2026-10-10
- Shared benchmarks: 24

## Summary

- They share 24 benchmarks with published results for both. GLM-4.6 scores higher in 8 categories and Mistral Medium in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-4.6 leads 39.6 to 24.9.
- The biggest single-benchmark swing is Berkeley Function Calling Leaderboard: 72.4% for GLM-4.6 and 37.7% for Mistral Medium.
- GLM-4.6 is cheaper at $0.60 / $2.20 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium.
- Mistral Medium accepts more context: 262K tokens versus 205K.

## Snapshot

| | GLM-4.6 | Mistral Medium |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 40.9 | 36.0 |
| Rank | 132 | 211 |
| Context | 205K | 262K |
| Input $/M | $0.60 | $1.50 |
| Output $/M | $2.20 | $7.50 |
| Weights | Open | Open |

## Coding

- GLM-4.6: 39.9 (#137)
- Mistral Medium: 33.8 (#241)

| Benchmark | GLM-4.6 | Mistral Medium |
|---|---|---|
| SciCode | 38.4% | 40.2% |
| LMArena Coding | 1449 | 1434 |
| ALE-Bench | 340.82 | 763.98 |
| FrontierCode | — | 8% |
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1339 | — |
| WeirdML | — | 43.7% |

## Agentic & Tool Use

- GLM-4.6: 32.1 (#60)
- Mistral Medium: 28.1 (#84)

| Benchmark | GLM-4.6 | Mistral Medium |
|---|---|---|
| Berkeley Function Calling Leaderboard | 72.4% | 37.7% |
| Terminal-Bench | 24.5% | — |

## Reasoning

- GLM-4.6: 23.1 (#168)
- Mistral Medium: 23.3 (#165)

| Benchmark | GLM-4.6 | Mistral Medium |
|---|---|---|
| Kagi LLM Benchmark | 47.4% | 50% |
| CritPt | 1.1% | 0% |
| LMArena Hard Prompts | 1440 | 1426 |
| DTBench | — | 75.5% |
| LMCA | — | 26.1% |
| Surface Evolver Bench | — | 26.9% |

## Math

- GLM-4.6: 36.4 (#115)
- Mistral Medium: 27.2 (#238)

| Benchmark | GLM-4.6 | Mistral Medium |
|---|---|---|
| LMArena Math | 1431 | 1409 |
| FrontierMath (Feb 2025 set) | 3.8% | 0.3% |
| OTIS Mock AIME 2024-2025 | — | 32.2% |
| ProofBench | — | 9% |
| MATH Level 5 | — | 81.6% |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-4.6: 39.6 (#118)
- Mistral Medium: 24.9 (#260)

| Benchmark | GLM-4.6 | Mistral Medium |
|---|---|---|
| Vectara Hallucination Rate | 9.5% | 22.7% |
| LMArena Expert | 1432 | 1408 |
| GPQA Diamond | — | 59.5% |
| Humanity's Last Exam | — | 4.5% |

## Multimodal

- GLM-4.6: —
- Mistral Medium: 34.6 (#82)

| Benchmark | GLM-4.6 | Mistral Medium |
|---|---|---|
| LMArena Vision | — | 1172 |

## Multilingual

- GLM-4.6: 53.6 (#62)
- Mistral Medium: 52.3 (#86)

| Benchmark | GLM-4.6 | Mistral Medium |
|---|---|---|
| LMArena Non-English | 1426 | 1408 |
| LMArena Chinese | 1500 | 1448 |
| LMArena French | 1459 | 1460 |
| LMArena German | 1447 | 1433 |
| LMArena Japanese | 1394 | 1378 |
| LMArena Korean | 1401 | 1382 |
| LMArena Russian | 1418 | 1411 |
| LMArena Spanish | 1436 | 1433 |

## Instruction Following

- GLM-4.6: 74.5 (#93)
- Mistral Medium: 73.9 (#111)

| Benchmark | GLM-4.6 | Mistral Medium |
|---|---|---|
| LMArena Instruction Following | 1410 | 1398 |

## Long Context

- GLM-4.6: 43.4 (#91)
- Mistral Medium: 42.9 (#108)

| Benchmark | GLM-4.6 | Mistral Medium |
|---|---|---|
| LMArena Longer Query | 1423 | 1406 |

## Writing & Preference

- GLM-4.6: 61.3 (#86)
- Mistral Medium: 60.2 (#97)

| Benchmark | GLM-4.6 | Mistral Medium |
|---|---|---|
| LMArena Text | 1440 | 1424 |
| LMArena Creative Writing | 1411 | 1391 |
| LMArena Multi-Turn | 1427 | 1418 |
| Short-Story Creative Writing | — | 77.3% |
| EQ-Bench Creative Writing | 1411 | — |

## FAQ

### Is GLM-4.6 better than Mistral Medium?

GLM-4.6 is the stronger model overall, scoring 40.9 to 36.0 on the Noometry Index.

### Which is cheaper, GLM-4.6 or Mistral Medium?

GLM-4.6 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Mistral Medium lists at $1.50 and $7.50.

### Is GLM-4.6 or Mistral Medium better for coding?

GLM-4.6 scores higher on coding benchmarks: 39.9 versus 33.8 in the Noometry coding category.

### Which has the bigger context window?

Mistral Medium does, with 262K tokens against 205K.

### How many benchmarks do GLM-4.6 and Mistral Medium share?

24 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Mistral Medium has 36.