# GLM-5.1 vs Mistral Small 3.1

> GLM-5.1 is the stronger model overall, scoring 47.6 to 31.4 on the Noometry Index. Mistral Small 3.1 costs 5.3× less per token, which makes it the better buy when GLM-5.1's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-5-1-vs-mistral-small-3-1
- Last updated: 2026-10-10
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. GLM-5.1 scores higher in 8 categories and Mistral Small 3.1 in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.1 leads 49.0 to 13.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 93.3% for GLM-5.1 and 3.9% for Mistral Small 3.1.
- Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $1.40 / $4.40 for GLM-5.1.
- GLM-5.1 accepts more context: 200K tokens versus 128K.

## Snapshot

| | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 47.6 | 31.4 |
| Rank | 51 | 263 |
| Context | 200K | 128K |
| Input $/M | $1.40 | $0.35 |
| Output $/M | $4.40 | $0.56 |
| Weights | Open | Open |

## Coding

- GLM-5.1: 48.5 (#52)
- Mistral Small 3.1: 37.7 (#175)

| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Coding | 1486 | 1309 |
| SWE-bench Verified | 74.2% | — |
| LMArena WebDev | 1509 | — |
| SciCode | 43.8% | — |
| WeirdML | 57.1% | — |
| ALE-Bench | 887.1 | — |

## Agentic & Tool Use

- GLM-5.1: 24.8 (#106)
- Mistral Small 3.1: —

| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| APEX-Agents | 40.9% | — |
| ExploitBench | 18.1% | — |
| GBAEval | 0% | — |
| Vending-Bench 2 | 5,634 | — |

## Reasoning

- GLM-5.1: 38.2 (#57)
- Mistral Small 3.1: 18.9 (#249)

| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| Chess Puzzles | 19% | 1% |
| LMArena Hard Prompts | 1472 | 1278 |
| Epoch Capabilities Index | 149.86 | 127.48 |
| SimpleBench | 55.1% | — |
| NYT Connections (extended) | 77.7% | — |
| CritPt | 4.6% | — |
| Thematic Generalization | 69.8% | — |

## Math

- GLM-5.1: 49.0 (#48)
- Mistral Small 3.1: 13.7 (#295)

| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 93.3% | 3.9% |
| LMArena Math | 1472 | 1261 |
| FrontierMath (Tiers 1-3) | 36.8% | — |
| MathArena Final-Answer Competitions | 67.1% | — |
| ProofBench | 22.2% | — |
| Omni-MATH | — | 24.8% |
| FrontierMath (Feb 2025 set) | 33.4% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |

## Knowledge

- GLM-5.1: 55.0 (#45)
- Mistral Small 3.1: 22.6 (#266)

| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| GPQA Diamond | 89.9% | 41.9% |
| LMArena Expert | 1477 | 1258 |
| SimpleQA Verified | 34% | — |
| MMLU-Pro | — | 61% |
| GPQA (HELM) | — | 39.2% |

## Multimodal

- GLM-5.1: —
- Mistral Small 3.1: 32.6 (#93)

| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Vision | — | 1136 |

## Multilingual

- GLM-5.1: 55.2 (#34)
- Mistral Small 3.1: 41.4 (#204)

| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Non-English | 1448 | 1255 |
| LMArena Chinese | 1516 | 1254 |
| LMArena French | 1478 | 1270 |
| LMArena German | 1466 | 1266 |
| LMArena Japanese | 1436 | 1210 |
| LMArena Korean | 1423 | 1206 |
| LMArena Russian | 1453 | 1263 |
| LMArena Spanish | 1467 | 1283 |

## Instruction Following

- GLM-5.1: 76.5 (#41)
- Mistral Small 3.1: 63.8 (#225)

| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Instruction Following | 1451 | 1264 |
| IFEval | — | 75% |

## Long Context

- GLM-5.1: 44.9 (#51)
- Mistral Small 3.1: 39.5 (#172)

| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Longer Query | 1467 | 1300 |

## Writing & Preference

- GLM-5.1: 67.2 (#29)
- Mistral Small 3.1: 37.2 (#254)

| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Text | 1462 | 1278 |
| LMArena Creative Writing | 1454 | 1253 |
| EQ-Bench Creative Writing | 1592 | 761 |
| LMArena Multi-Turn | 1473 | 1270 |
| WildBench | — | 78.8% |

## FAQ

### Is GLM-5.1 better than Mistral Small 3.1?

GLM-5.1 is the stronger model overall, scoring 47.6 to 31.4 on the Noometry Index. Mistral Small 3.1 costs 5.3× less per token, which makes it the better buy when GLM-5.1's lead doesn't matter for your workload.

### Which is cheaper, GLM-5.1 or Mistral Small 3.1?

Mistral Small 3.1 is cheaper. It lists at $0.35 per million input tokens and $0.56 per million output tokens; GLM-5.1 lists at $1.40 and $4.40.

### Is GLM-5.1 or Mistral Small 3.1 better for coding?

GLM-5.1 scores higher on coding benchmarks: 48.5 versus 37.7 in the Noometry coding category.

### Which has the bigger context window?

GLM-5.1 does, with 200K tokens against 128K.

### How many benchmarks do GLM-5.1 and Mistral Small 3.1 share?

22 benchmarks have published results for both models. GLM-5.1 has 41 scored results on Noometry and Mistral Small 3.1 has 28.