Model comparison
GPT-3.5-turbo vs Trinity Large Thinking
Trinity Large Thinking is the stronger model overall, scoring 38.6 to 23.2 on the Noometry Index.
Last verified . 17 shared benchmarks.
Arcee AISummary
- They share 17 benchmarks with published results for both. GPT-3.5-turbo scores higher in 0 categories and Trinity Large Thinking in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Trinity Large Thinking leads 37.6 to 6.3.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $0.50 / $1.50 for GPT-3.5-turbo.
- Trinity Large Thinking accepts more context: 262K tokens versus 16K.
- Trinity Large Thinking has downloadable open weights; the other is API-only.
Side by side
| GPT-3.5-turbo | Trinity Large Thinking | |
|---|---|---|
| Provider | OpenAI | Arcee AI |
| Noometry Index | 23.2 | 38.6 |
| Released | 2023-03-01 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 16K | 262K |
| Max output | 4K | 80K |
| Input $ / M tokens | $0.50 | $0.25 |
| Output $ / M tokens | $1.50 | $0.80 |
| Results tracked | 44 | 24 |
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Category by category
Coding Trinity Large Thinking leads
GPT-3.5-turbo: 23.9 (#331), Trinity Large Thinking: 34.1 (#244)
| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Coding | 1136 | 1381 |
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |
| WeirdML | 3.5% | — |
| BigCodeBench Instruct | 39.1% | — |
| BigCodeBench Complete | 50.6% | — |
| HumanEval+ | 70.7% | — |
| MBPP+ | 69.7% | — |
Agentic & Tool Use Not comparable
GPT-3.5-turbo: —, Trinity Large Thinking: —
| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| METR Time Horizons | 21.5% | — |
Reasoning Trinity Large Thinking leads
GPT-3.5-turbo: 13.8 (#332), Trinity Large Thinking: 16.9 (#298)
| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Hard Prompts | 1108 | 1350 |
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Chess Puzzles | 0% | — |
| Thematic Generalization | — | 41.6% |
| Mystery Game Puzzles | 3% | — |
| DTBench | 48.5% | — |
| LMCA | 9.7% | — |
| Surface Evolver Bench | — | 15.6% |
| Adversarial NLI | 58.1% | — |
| BIG-Bench Hard | 61.6% | — |
| CommonsenseQA 2.0 | 57% | — |
| Epoch Capabilities Index | 118.55 | — |
| ForecastBench | 50.4 | — |
| WinoGrande | 81.6% | — |
Math Trinity Large Thinking leads
GPT-3.5-turbo: 6.3 (#327), Trinity Large Thinking: 37.6 (#149)
| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1142 | 1366 |
| FrontierMath (Tiers 1-3) | 0% | — |
| OTIS Mock AIME 2024-2025 | 2.2% | — |
| MATH Level 5 | 15.9% | — |
| GSM8K | 57.8% | — |
Knowledge Trinity Large Thinking leads
GPT-3.5-turbo: 10.0 (#303), Trinity Large Thinking: 40.9 (#113)
| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Expert | 1070 | 1360 |
| GPQA Diamond | 28% | — |
| Vectara Hallucination Rate | — | 6.9% |
| ARC (AI2) Challenge | 87.4% | — |
| BoolQ | 87% | — |
| MMLU | 71.4% | — |
| OpenBookQA | 86% | — |
| TriviaQA | 85.8% | — |
Multilingual Trinity Large Thinking leads
GPT-3.5-turbo: 31.5 (#258), Trinity Large Thinking: 46.2 (#160)
| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1108 | 1325 |
| LMArena Chinese | 1075 | 1373 |
| LMArena French | 1118 | 1374 |
| LMArena German | 1090 | 1356 |
| LMArena Japanese | 1043 | 1311 |
| LMArena Korean | 1019 | 1306 |
| LMArena Russian | 1123 | 1337 |
| LMArena Spanish | 1121 | 1357 |
Instruction Following Trinity Large Thinking leads
GPT-3.5-turbo: 57.9 (#262), Trinity Large Thinking: 70.5 (#162)
| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1119 | 1334 |
Long Context Trinity Large Thinking leads
GPT-3.5-turbo: 34.0 (#254), Trinity Large Thinking: 41.3 (#144)
| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1121 | 1355 |
Writing & Preference Trinity Large Thinking leads
GPT-3.5-turbo: 25.3 (#305), Trinity Large Thinking: 53.8 (#158)
| Benchmark | GPT-3.5-turbo | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1125 | 1340 |
| LMArena Creative Writing | 1092 | 1320 |
| LMArena Multi-Turn | 1117 | 1342 |
| EQ-Bench Creative Writing | 451 | — |
Frequently asked questions
Is GPT-3.5-turbo better than Trinity Large Thinking?
Trinity Large Thinking is the stronger model overall, scoring 38.6 to 23.2 on the Noometry Index.
Which is cheaper, GPT-3.5-turbo 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; GPT-3.5-turbo lists at $0.50 and $1.50.
Is GPT-3.5-turbo or Trinity Large Thinking better for coding?
Trinity Large Thinking scores higher on coding benchmarks: 34.1 versus 23.9 in the Noometry coding category.
Which has the bigger context window?
Trinity Large Thinking does, with 262K tokens against 16K.
How many benchmarks do GPT-3.5-turbo and Trinity Large Thinking share?
17 benchmarks have published results for both models. GPT-3.5-turbo has 44 scored results on Noometry and Trinity Large Thinking has 24.