Model comparison
Trinity Large Thinking vs Yi-1.5-34B
Trinity Large Thinking is the stronger model overall, scoring 38.1 to 30.2 on the Noometry Index.
Last verified . 17 shared benchmarks.
Arcee AISummary
- They share 17 benchmarks with published results for both. Trinity Large Thinking scores higher in 7 categories and Yi-1.5-34B in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Trinity Large Thinking leads 40.3 to 14.8.
Side by side
| Trinity Large Thinking | Yi-1.5-34B | |
|---|---|---|
| Provider | Arcee AI | 01.AI |
| Noometry Index | 38.1 | 30.2 |
| Released | 2026-04-01 | 2024-05-13 |
| Weights | Open | Open |
| Context window | 262K | — |
| Max output | 80K | — |
| Input $ / M tokens | $0.25 | — |
| Output $ / M tokens | $0.80 | — |
| Results tracked | 24 | 21 |
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Category by category
Coding Trinity Large Thinking leads
Trinity Large Thinking: 33.8 (#238), Yi-1.5-34B: 31.9 (#267)
| Benchmark | Trinity Large Thinking | Yi-1.5-34B |
|---|---|---|
| LMArena Coding | 1381 | 1169 |
| LMArena WebDev | 1238 | — |
| SciCode | 36.1% | — |
| BigCodeBench Instruct | — | 33.9% |
| BigCodeBench Complete | — | 43.8% |
Reasoning Yi-1.5-34B leads
Trinity Large Thinking: 16.3 (#298), Yi-1.5-34B: 21.5 (#195)
| Benchmark | Trinity Large Thinking | Yi-1.5-34B |
|---|---|---|
| LMArena Hard Prompts | 1350 | 1160 |
| NYT Connections (extended) | 16.5% | — |
| CritPt | 0.9% | — |
| Thematic Generalization | 41.6% | — |
| Surface Evolver Bench | 15.6% | — |
Math Trinity Large Thinking leads
Trinity Large Thinking: 34.9 (#149), Yi-1.5-34B: 25.3 (#248)
| Benchmark | Trinity Large Thinking | Yi-1.5-34B |
|---|---|---|
| LMArena Math | 1366 | 1182 |
| MATH Level 5 | — | 25.5% |
Knowledge Trinity Large Thinking leads
Trinity Large Thinking: 40.3 (#107), Yi-1.5-34B: 14.8 (#290)
| Benchmark | Trinity Large Thinking | Yi-1.5-34B |
|---|---|---|
| LMArena Expert | 1359 | 1144 |
| GPQA Diamond | — | 32% |
| Vectara Hallucination Rate | 6.9% | — |
Multilingual Trinity Large Thinking leads
Trinity Large Thinking: 46.4 (#155), Yi-1.5-34B: 32.5 (#251)
| Benchmark | Trinity Large Thinking | Yi-1.5-34B |
|---|---|---|
| LMArena Non-English | 1325 | 1121 |
| LMArena Chinese | 1372 | 1213 |
| LMArena French | 1374 | 1155 |
| LMArena German | 1356 | 1111 |
| LMArena Japanese | 1312 | 1021 |
| LMArena Korean | 1304 | 1005 |
| LMArena Russian | 1338 | 1091 |
| LMArena Spanish | 1356 | 1120 |
Instruction Following Trinity Large Thinking leads
Trinity Large Thinking: 70.7 (#157), Yi-1.5-34B: 59.4 (#252)
| Benchmark | Trinity Large Thinking | Yi-1.5-34B |
|---|---|---|
| LMArena Instruction Following | 1334 | 1139 |
Long Context Trinity Large Thinking leads
Trinity Large Thinking: 41.2 (#139), Yi-1.5-34B: 34.6 (#243)
| Benchmark | Trinity Large Thinking | Yi-1.5-34B |
|---|---|---|
| LMArena Longer Query | 1355 | 1144 |
Writing & Preference Trinity Large Thinking leads
Trinity Large Thinking: 54.0 (#152), Yi-1.5-34B: 37.6 (#252)
| Benchmark | Trinity Large Thinking | Yi-1.5-34B |
|---|---|---|
| LMArena Text | 1340 | 1173 |
| LMArena Creative Writing | 1321 | 1135 |
| LMArena Multi-Turn | 1342 | 1153 |
Frequently asked questions
Is Trinity Large Thinking better than Yi-1.5-34B?
Trinity Large Thinking is the stronger model overall, scoring 38.1 to 30.2 on the Noometry Index.
Is Trinity Large Thinking or Yi-1.5-34B better for coding?
Trinity Large Thinking scores higher on coding benchmarks: 33.8 versus 31.9 in the Noometry coding category.
How many benchmarks do Trinity Large Thinking and Yi-1.5-34B share?
17 benchmarks have published results for both models. Trinity Large Thinking has 24 scored results on Noometry and Yi-1.5-34B has 21.