Model comparison
Qwen2.5 32B Instruct vs Trinity Large Thinking
Trinity Large Thinking is the stronger model overall, scoring 38.6 to 30.1 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)
Arcee AISummary
- The widest gap is in math, where Trinity Large Thinking leads 37.6 to 16.2.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $0.70 / $2.80 for Qwen2.5 32B Instruct.
- Trinity Large Thinking accepts more context: 262K tokens versus 131K.
Side by side
| Qwen2.5 32B Instruct | Trinity Large Thinking | |
|---|---|---|
| Provider | Alibaba (Qwen) | Arcee AI |
| Noometry Index | 30.1 | 38.6 |
| Released | 2024-09 | 2026-04-01 |
| Weights | Open | Open |
| Context window | 131K | 262K |
| Max output | 8K | 80K |
| Input $ / M tokens | $0.70 | $0.25 |
| Output $ / M tokens | $2.80 | $0.80 |
| Results tracked | 7 | 24 |
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Category by category
Coding Qwen2.5 32B Instruct leads
Qwen2.5 32B Instruct: 38.7 (#169), Trinity Large Thinking: 34.1 (#244)
| Benchmark | Qwen2.5 32B Instruct | Trinity Large Thinking |
|---|---|---|
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |
| BigCodeBench Instruct | 45% | — |
| LMArena Coding | — | 1381 |
| BigCodeBench Complete | 52.3% | — |
Reasoning Qwen2.5 32B Instruct leads
Qwen2.5 32B Instruct: 19.2 (#266), Trinity Large Thinking: 16.9 (#298)
| Benchmark | Qwen2.5 32B Instruct | 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% |
| Epoch Capabilities Index | 128.52 | — |
Math Trinity Large Thinking leads
Qwen2.5 32B Instruct: 16.2 (#296), Trinity Large Thinking: 37.6 (#149)
| Benchmark | Qwen2.5 32B Instruct | Trinity Large Thinking |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 7.4% | — |
| LMArena Math | — | 1366 |
| MATH Level 5 | 56.1% | — |
Knowledge Trinity Large Thinking leads
Qwen2.5 32B Instruct: 24.9 (#266), Trinity Large Thinking: 40.9 (#113)
| Benchmark | Qwen2.5 32B Instruct | Trinity Large Thinking |
|---|---|---|
| GPQA Diamond | 46.1% | — |
| Vectara Hallucination Rate | — | 6.9% |
| LMArena Expert | — | 1360 |
Multilingual Not comparable
Qwen2.5 32B Instruct: —, Trinity Large Thinking: 46.2 (#160)
| Benchmark | Qwen2.5 32B Instruct | 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 Not comparable
Qwen2.5 32B Instruct: —, Trinity Large Thinking: 70.5 (#162)
| Benchmark | Qwen2.5 32B Instruct | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | — | 1334 |
Long Context Not comparable
Qwen2.5 32B Instruct: —, Trinity Large Thinking: 41.3 (#144)
| Benchmark | Qwen2.5 32B Instruct | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | — | 1355 |
Writing & Preference Not comparable
Qwen2.5 32B Instruct: —, Trinity Large Thinking: 53.8 (#158)
| Benchmark | Qwen2.5 32B Instruct | Trinity Large Thinking |
|---|---|---|
| LMArena Text | — | 1340 |
| LMArena Creative Writing | — | 1320 |
| LMArena Multi-Turn | — | 1342 |
Frequently asked questions
Is Qwen2.5 32B Instruct better than Trinity Large Thinking?
Trinity Large Thinking is the stronger model overall, scoring 38.6 to 30.1 on the Noometry Index.
Which is cheaper, Qwen2.5 32B 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 32B Instruct lists at $0.70 and $2.80.
Is Qwen2.5 32B Instruct or Trinity Large Thinking better for coding?
Qwen2.5 32B Instruct scores higher on coding benchmarks: 38.7 versus 34.1 in the Noometry coding category.
Which has the bigger context window?
Trinity Large Thinking does, with 262K tokens against 131K.
How many benchmarks do Qwen2.5 32B Instruct and Trinity Large Thinking share?
0 benchmarks have published results for both models. Qwen2.5 32B Instruct has 7 scored results on Noometry and Trinity Large Thinking has 24.