# Qwen1.5-7B vs Trinity Large Thinking

> Trinity Large Thinking is the stronger model overall, scoring 38.6 to 31.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/qwen1-5-7b-vs-trinity-large-thinking
- Last updated: 2026-10-11
- Shared benchmarks: 12

## Summary

- They share 12 benchmarks with published results for both. Qwen1.5-7B scores higher in 1 category and Trinity Large Thinking in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Trinity Large Thinking leads 53.8 to 29.6.

## Snapshot

| | Qwen1.5-7B | Trinity Large Thinking |
|---|---|---|
| Provider | Alibaba (Qwen) | Arcee AI |
| Noometry Index | 31.4 | 38.6 |
| Rank | 273 | 185 |
| Context | — | 262K |
| Input $/M | — | $0.25 |
| Output $/M | — | $0.80 |
| Weights | Open | Open |

## Coding

- Qwen1.5-7B: 32.2 (#276)
- Trinity Large Thinking: 34.1 (#244)

| Benchmark | Qwen1.5-7B | Trinity Large Thinking |
|---|---|---|
| LMArena Coding | 1107 | 1381 |
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |

## Reasoning

- Qwen1.5-7B: 20.4 (#240)
- Trinity Large Thinking: 16.9 (#298)

| Benchmark | Qwen1.5-7B | Trinity Large Thinking |
|---|---|---|
| LMArena Hard Prompts | 1065 | 1350 |
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Thematic Generalization | — | 41.6% |
| Surface Evolver Bench | — | 15.6% |

## Math

- Qwen1.5-7B: 31.4 (#224)
- Trinity Large Thinking: 37.6 (#149)

| Benchmark | Qwen1.5-7B | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1080 | 1366 |

## Knowledge

- Qwen1.5-7B: 28.7 (#243)
- Trinity Large Thinking: 40.9 (#113)

| Benchmark | Qwen1.5-7B | Trinity Large Thinking |
|---|---|---|
| LMArena Expert | 1055 | 1360 |
| Vectara Hallucination Rate | — | 6.9% |
| MMLU | 62.6% | — |

## Multilingual

- Qwen1.5-7B: 28.5 (#271)
- Trinity Large Thinking: 46.2 (#160)

| Benchmark | Qwen1.5-7B | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1058 | 1325 |
| LMArena Chinese | 1141 | 1373 |
| LMArena Russian | 1006 | 1337 |
| LMArena French | — | 1374 |
| LMArena German | — | 1356 |
| LMArena Japanese | — | 1311 |
| LMArena Korean | — | 1306 |
| LMArena Spanish | — | 1357 |

## Instruction Following

- Qwen1.5-7B: 54.1 (#281)
- Trinity Large Thinking: 70.5 (#162)

| Benchmark | Qwen1.5-7B | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1058 | 1334 |

## Long Context

- Qwen1.5-7B: 33.1 (#266)
- Trinity Large Thinking: 41.3 (#144)

| Benchmark | Qwen1.5-7B | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1090 | 1355 |

## Writing & Preference

- Qwen1.5-7B: 29.6 (#293)
- Trinity Large Thinking: 53.8 (#158)

| Benchmark | Qwen1.5-7B | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1083 | 1340 |
| LMArena Creative Writing | 1035 | 1320 |
| LMArena Multi-Turn | 1062 | 1342 |

## FAQ

### Is Qwen1.5-7B better than Trinity Large Thinking?

Trinity Large Thinking is the stronger model overall, scoring 38.6 to 31.4 on the Noometry Index.

### Is Qwen1.5-7B or Trinity Large Thinking better for coding?

Trinity Large Thinking scores higher on coding benchmarks: 34.1 versus 32.2 in the Noometry coding category.

### How many benchmarks do Qwen1.5-7B and Trinity Large Thinking share?

12 benchmarks have published results for both models. Qwen1.5-7B has 13 scored results on Noometry and Trinity Large Thinking has 24.