# Qwen3-1.7B vs Trinity Large Thinking

> Trinity Large Thinking is the stronger model overall, scoring 38.6 to 26.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/qwen3-1-7b-vs-trinity-large-thinking
- Last updated: 2026-10-12
- Shared benchmarks: 0

## Summary

- The widest gap is in knowledge, where Trinity Large Thinking leads 40.9 to 19.6.

## Snapshot

| | Qwen3-1.7B | Trinity Large Thinking |
|---|---|---|
| Provider | Alibaba (Qwen) | Arcee AI |
| Noometry Index | 26.6 | 38.6 |
| Rank | 336 | 185 |
| Context | — | 262K |
| Input $/M | — | $0.25 |
| Output $/M | — | $0.80 |
| Weights | Open | Open |

## Coding

- Qwen3-1.7B: —
- Trinity Large Thinking: 34.1 (#244)

| Benchmark | Qwen3-1.7B | Trinity Large Thinking |
|---|---|---|
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |
| LMArena Coding | — | 1381 |

## Agentic & Tool Use

- Qwen3-1.7B: 24.7 (#115)
- Trinity Large Thinking: —

| Benchmark | Qwen3-1.7B | Trinity Large Thinking |
|---|---|---|
| Berkeley Function Calling Leaderboard | 28.4% | — |

## Reasoning

- Qwen3-1.7B: 19.2 (#267)
- Trinity Large Thinking: 16.9 (#298)

| Benchmark | Qwen3-1.7B | Trinity Large Thinking |
|---|---|---|
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Chess Puzzles | 0% | — |
| Thematic Generalization | — | 41.6% |
| LMArena Hard Prompts | — | 1350 |
| Surface Evolver Bench | — | 15.6% |

## Math

- Qwen3-1.7B: 16.3 (#294)
- Trinity Large Thinking: 37.6 (#149)

| Benchmark | Qwen3-1.7B | Trinity Large Thinking |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 8.1% | — |
| LMArena Math | — | 1366 |

## Knowledge

- Qwen3-1.7B: 19.6 (#278)
- Trinity Large Thinking: 40.9 (#113)

| Benchmark | Qwen3-1.7B | Trinity Large Thinking |
|---|---|---|
| GPQA Diamond | 38% | — |
| Vectara Hallucination Rate | — | 6.9% |
| LMArena Expert | — | 1360 |

## Multilingual

- Qwen3-1.7B: —
- Trinity Large Thinking: 46.2 (#160)

| Benchmark | Qwen3-1.7B | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | — | 1325 |
| LMArena Chinese | — | 1373 |
| LMArena French | — | 1374 |
| LMArena German | — | 1356 |
| LMArena Japanese | — | 1311 |
| LMArena Korean | — | 1306 |
| LMArena Russian | — | 1337 |
| LMArena Spanish | — | 1357 |

## Instruction Following

- Qwen3-1.7B: —
- Trinity Large Thinking: 70.5 (#162)

| Benchmark | Qwen3-1.7B | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | — | 1334 |

## Long Context

- Qwen3-1.7B: —
- Trinity Large Thinking: 41.3 (#144)

| Benchmark | Qwen3-1.7B | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | — | 1355 |

## Writing & Preference

- Qwen3-1.7B: —
- Trinity Large Thinking: 53.8 (#158)

| Benchmark | Qwen3-1.7B | Trinity Large Thinking |
|---|---|---|
| LMArena Text | — | 1340 |
| LMArena Creative Writing | — | 1320 |
| LMArena Multi-Turn | — | 1342 |

## FAQ

### Is Qwen3-1.7B better than Trinity Large Thinking?

Trinity Large Thinking is the stronger model overall, scoring 38.6 to 26.6 on the Noometry Index.

### How many benchmarks do Qwen3-1.7B and Trinity Large Thinking share?

0 benchmarks have published results for both models. Qwen3-1.7B has 4 scored results on Noometry and Trinity Large Thinking has 24.