# Qwen2.5 72B Instruct vs Trinity Large Thinking

> Trinity Large Thinking is the stronger model overall, scoring 38.6 to 31.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/qwen2-5-72b-instruct-vs-trinity-large-thinking
- Last updated: 2026-10-12
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. Qwen2.5 72B Instruct scores higher in 1 category and Trinity Large Thinking in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Trinity Large Thinking leads 37.6 to 19.3.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $1.40 / $5.60 for Qwen2.5 72B Instruct.
- Trinity Large Thinking accepts more context: 262K tokens versus 131K.

## Snapshot

| | Qwen2.5 72B Instruct | Trinity Large Thinking |
|---|---|---|
| Provider | Alibaba (Qwen) | Arcee AI |
| Noometry Index | 31.9 | 38.6 |
| Rank | 267 | 185 |
| Context | 131K | 262K |
| Input $/M | $1.40 | $0.25 |
| Output $/M | $5.60 | $0.80 |
| Weights | Open | Open |

## Coding

- Qwen2.5 72B Instruct: 33.2 (#260)
- Trinity Large Thinking: 34.1 (#244)

| Benchmark | Qwen2.5 72B Instruct | Trinity Large Thinking |
|---|---|---|
| LMArena Coding | 1292 | 1381 |
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |
| WeirdML | 16% | — |
| BigCodeBench Instruct | 45.8% | — |
| BigCodeBench Complete | 55.9% | — |

## Agentic & Tool Use

- Qwen2.5 72B Instruct: 22.1 (#133)
- Trinity Large Thinking: —

| Benchmark | Qwen2.5 72B Instruct | Trinity Large Thinking |
|---|---|---|
| TheAgentCompany | 5.7% | — |
| BALROG | 16.2% | — |
| METR Time Horizons | 35.8% | — |

## Reasoning

- Qwen2.5 72B Instruct: 22.3 (#199)
- Trinity Large Thinking: 16.9 (#298)

| Benchmark | Qwen2.5 72B Instruct | Trinity Large Thinking |
|---|---|---|
| LMArena Hard Prompts | 1271 | 1350 |
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Thematic Generalization | — | 41.6% |
| DTBench | 62.9% | — |
| LMCA | 13.4% | — |
| Surface Evolver Bench | — | 15.6% |
| BIG-Bench Hard | 79.8% | — |
| Epoch Capabilities Index | 129 | — |
| ForecastBench | 57.5 | — |
| HellaSwag | 84.8% | — |
| PIQA | 82.6% | — |
| WinoGrande | 82.3% | — |

## Math

- Qwen2.5 72B Instruct: 19.3 (#287)
- Trinity Large Thinking: 37.6 (#149)

| Benchmark | Qwen2.5 72B Instruct | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1283 | 1366 |
| OTIS Mock AIME 2024-2025 | 8.1% | — |
| Omni-MATH | 33% | — |
| MATH Level 5 | 63.2% | — |

## Knowledge

- Qwen2.5 72B Instruct: 27.0 (#253)
- Trinity Large Thinking: 40.9 (#113)

| Benchmark | Qwen2.5 72B Instruct | Trinity Large Thinking |
|---|---|---|
| LMArena Expert | 1245 | 1360 |
| GPQA Diamond | 49.1% | — |
| MMLU-Pro | 63.1% | — |
| Confabulations | 19.1% | — |
| Vectara Hallucination Rate | — | 6.9% |
| GPQA (HELM) | 42.6% | — |
| ARC (AI2) Challenge | 94.5% | — |
| MMLU | 85.3% | — |
| TriviaQA | 71.9% | — |

## Multilingual

- Qwen2.5 72B Instruct: 41.0 (#213)
- Trinity Large Thinking: 46.2 (#160)

| Benchmark | Qwen2.5 72B Instruct | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1252 | 1325 |
| LMArena Chinese | 1272 | 1373 |
| LMArena French | 1280 | 1374 |
| LMArena German | 1234 | 1356 |
| LMArena Japanese | 1180 | 1311 |
| LMArena Korean | 1188 | 1306 |
| LMArena Russian | 1264 | 1337 |
| LMArena Spanish | 1256 | 1357 |

## Instruction Following

- Qwen2.5 72B Instruct: 65.5 (#221)
- Trinity Large Thinking: 70.5 (#162)

| Benchmark | Qwen2.5 72B Instruct | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1254 | 1334 |
| IFEval | 80.6% | — |

## Long Context

- Qwen2.5 72B Instruct: 38.9 (#188)
- Trinity Large Thinking: 41.3 (#144)

| Benchmark | Qwen2.5 72B Instruct | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1282 | 1355 |

## Writing & Preference

- Qwen2.5 72B Instruct: 46.7 (#215)
- Trinity Large Thinking: 53.8 (#158)

| Benchmark | Qwen2.5 72B Instruct | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1269 | 1340 |
| LMArena Creative Writing | 1221 | 1320 |
| LMArena Multi-Turn | 1272 | 1342 |
| WildBench | 80.2% | — |

## FAQ

### Is Qwen2.5 72B Instruct better than Trinity Large Thinking?

Trinity Large Thinking is the stronger model overall, scoring 38.6 to 31.9 on the Noometry Index.

### Which is cheaper, Qwen2.5 72B Instruct or Trinity Large Thinking?

Trinity Large Thinking is cheaper. It lists at $0.25 per million input tokens and $0.80 per million output tokens; Qwen2.5 72B Instruct lists at $1.40 and $5.60.

### Is Qwen2.5 72B Instruct or Trinity Large Thinking better for coding?

They score almost the same on coding (33.2 vs 34.1); test both on your own repository before choosing.

### Which has the bigger context window?

Trinity Large Thinking does, with 262K tokens against 131K.

### How many benchmarks do Qwen2.5 72B Instruct and Trinity Large Thinking share?

17 benchmarks have published results for both models. Qwen2.5 72B Instruct has 43 scored results on Noometry and Trinity Large Thinking has 24.