# Mistral vs Trinity Large Thinking

> Trinity Large Thinking is the stronger model overall, scoring 38.6 to 29.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/mistral-vs-trinity-large-thinking
- Last updated: 2026-10-11
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. Mistral scores higher in 1 category and Trinity Large Thinking in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Trinity Large Thinking leads 40.9 to 16.6.
- Trinity Large Thinking has downloadable open weights; the other is API-only.

## Snapshot

| | Mistral | Trinity Large Thinking |
|---|---|---|
| Provider | Mistral AI | Arcee AI |
| Noometry Index | 29.9 | 38.6 |
| Rank | 303 | 185 |
| Context | — | 262K |
| Input $/M | — | $0.25 |
| Output $/M | — | $0.80 |
| Weights | Proprietary | Open |

## Coding

- Mistral: 33.8 (#250)
- Trinity Large Thinking: 34.1 (#244)

| Benchmark | Mistral | Trinity Large Thinking |
|---|---|---|
| LMArena Coding | 1162 | 1381 |
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |

## Reasoning

- Mistral: 22.2 (#200)
- Trinity Large Thinking: 16.9 (#298)

| Benchmark | Mistral | Trinity Large Thinking |
|---|---|---|
| LMArena Hard Prompts | 1149 | 1350 |
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Thematic Generalization | — | 41.6% |
| Surface Evolver Bench | — | 15.6% |

## Math

- Mistral: 22.3 (#278)
- Trinity Large Thinking: 37.6 (#149)

| Benchmark | Mistral | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1180 | 1366 |
| Omni-MATH | 7.2% | — |

## Knowledge

- Mistral: 16.6 (#288)
- Trinity Large Thinking: 40.9 (#113)

| Benchmark | Mistral | Trinity Large Thinking |
|---|---|---|
| LMArena Expert | 1125 | 1360 |
| MMLU-Pro | 27.7% | — |
| Vectara Hallucination Rate | — | 6.9% |
| GPQA (HELM) | 30.3% | — |

## Multilingual

- Mistral: 32.8 (#254)
- Trinity Large Thinking: 46.2 (#160)

| Benchmark | Mistral | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1129 | 1325 |
| LMArena Chinese | 1109 | 1373 |
| LMArena French | 1180 | 1374 |
| LMArena German | 1155 | 1356 |
| LMArena Japanese | 1013 | 1311 |
| LMArena Korean | 1032 | 1306 |
| LMArena Russian | 1168 | 1337 |
| LMArena Spanish | 1143 | 1357 |

## Instruction Following

- Mistral: 52.6 (#288)
- Trinity Large Thinking: 70.5 (#162)

| Benchmark | Mistral | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1152 | 1334 |
| IFEval | 56.8% | — |

## Long Context

- Mistral: 35.0 (#245)
- Trinity Large Thinking: 41.3 (#144)

| Benchmark | Mistral | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1153 | 1355 |

## Writing & Preference

- Mistral: 37.0 (#260)
- Trinity Large Thinking: 53.8 (#158)

| Benchmark | Mistral | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1165 | 1340 |
| LMArena Creative Writing | 1158 | 1320 |
| LMArena Multi-Turn | 1147 | 1342 |
| WildBench | 66% | — |

## FAQ

### Is Mistral better than Trinity Large Thinking?

Trinity Large Thinking is the stronger model overall, scoring 38.6 to 29.9 on the Noometry Index.

### Is Mistral or Trinity Large Thinking better for coding?

They score almost the same on coding (33.8 vs 34.1); test both on your own repository before choosing.

### How many benchmarks do Mistral and Trinity Large Thinking share?

17 benchmarks have published results for both models. Mistral has 22 scored results on Noometry and Trinity Large Thinking has 24.