Model comparison
GPT-4.1 mini vs Trinity Large Thinking
Trinity Large Thinking is the stronger model overall, scoring 38.6 to 33.6 on the Noometry Index.
Last verified . 19 shared benchmarks.
Arcee AISummary
- They share 19 benchmarks with published results for both. GPT-4.1 mini 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 24.1.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $0.40 / $1.60 for GPT-4.1 mini.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 262K.
- Trinity Large Thinking has downloadable open weights; the other is API-only.
Side by side
| GPT-4.1 mini | Trinity Large Thinking | |
|---|---|---|
| Provider | OpenAI | Arcee AI |
| Noometry Index | 33.6 | 38.6 |
| Released | 2025-04-14 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 33K | 80K |
| Input $ / M tokens | $0.40 | $0.25 |
| Output $ / M tokens | $1.60 | $0.80 |
| Results tracked | 47 | 24 |
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Category by category
Coding Trinity Large Thinking leads
GPT-4.1 mini: 30.6 (#293), Trinity Large Thinking: 34.1 (#244)
| Benchmark | GPT-4.1 mini | Trinity Large Thinking |
|---|---|---|
| SciCode | 40.4% | 36.1% |
| LMArena Coding | 1367 | 1381 |
| SWE-bench Verified (bash only) | 23.9% | — |
| Aider Polyglot | 32.4% | — |
| LMArena WebDev | — | 1238 |
| WeirdML | 37.6% | — |
| BigCodeBench Instruct | 48.9% | — |
| CadEval | 16% | — |
Agentic & Tool Use Not comparable
GPT-4.1 mini: 33.3 (#55), Trinity Large Thinking: —
| Benchmark | GPT-4.1 mini | Trinity Large Thinking |
|---|---|---|
| Berkeley Function Calling Leaderboard | 50.5% | — |
Reasoning Trinity Large Thinking leads
GPT-4.1 mini: 10.8 (#340), Trinity Large Thinking: 16.9 (#298)
| Benchmark | GPT-4.1 mini | Trinity Large Thinking |
|---|---|---|
| CritPt | 0% | 0.9% |
| LMArena Hard Prompts | 1349 | 1350 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 48.6% | — |
| NYT Connections (extended) | — | 16.5% |
| ARC-AGI-1 | 3.5% | — |
| Chess Puzzles | 7% | — |
| Thematic Generalization | — | 41.6% |
| Mystery Game Puzzles | 7% | — |
| DTBench | 68.8% | — |
| LMCA | 21.1% | — |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 135.01 | — |
Math Trinity Large Thinking leads
GPT-4.1 mini: 24.1 (#270), Trinity Large Thinking: 37.6 (#149)
| Benchmark | GPT-4.1 mini | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1343 | 1366 |
| FrontierMath (Tiers 1-3) | 6.7% | — |
| OTIS Mock AIME 2024-2025 | 44.7% | — |
| Omni-MATH | 49.1% | — |
| MATH Level 5 | 87.3% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
Knowledge Trinity Large Thinking leads
GPT-4.1 mini: 34.7 (#194), Trinity Large Thinking: 40.9 (#113)
| Benchmark | GPT-4.1 mini | Trinity Large Thinking |
|---|---|---|
| LMArena Expert | 1338 | 1360 |
| GPQA Diamond | 65.8% | — |
| SimpleQA Verified | 12.7% | — |
| MMLU-Pro | 78.3% | — |
| Vectara Hallucination Rate | — | 6.9% |
| GPQA (HELM) | 61.4% | — |
Multimodal Not comparable
GPT-4.1 mini: 35.8 (#82), Trinity Large Thinking: —
| Benchmark | GPT-4.1 mini | Trinity Large Thinking |
|---|---|---|
| LMArena Vision | 1181 | — |
Multilingual Too close to call
GPT-4.1 mini: 45.7 (#166), Trinity Large Thinking: 46.2 (#160)
| Benchmark | GPT-4.1 mini | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1318 | 1325 |
| LMArena Chinese | 1329 | 1373 |
| LMArena French | 1358 | 1374 |
| LMArena German | 1351 | 1356 |
| LMArena Japanese | 1290 | 1311 |
| LMArena Korean | 1298 | 1306 |
| LMArena Russian | 1324 | 1337 |
| LMArena Spanish | 1319 | 1357 |
Instruction Following GPT-4.1 mini leads
GPT-4.1 mini: 73.7 (#118), Trinity Large Thinking: 70.5 (#162)
| Benchmark | GPT-4.1 mini | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1333 | 1334 |
| IFEval | 90.4% | — |
Long Context Trinity Large Thinking leads
GPT-4.1 mini: 31.8 (#275), Trinity Large Thinking: 41.3 (#144)
| Benchmark | GPT-4.1 mini | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1344 | 1355 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference Trinity Large Thinking leads
GPT-4.1 mini: 48.6 (#199), Trinity Large Thinking: 53.8 (#158)
| Benchmark | GPT-4.1 mini | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1340 | 1340 |
| LMArena Creative Writing | 1300 | 1320 |
| LMArena Multi-Turn | 1354 | 1342 |
| EQ-Bench Creative Writing | 1147 | — |
| WildBench | 83.8% | — |
Frequently asked questions
Is GPT-4.1 mini better than Trinity Large Thinking?
Trinity Large Thinking is the stronger model overall, scoring 38.6 to 33.6 on the Noometry Index.
Which is cheaper, GPT-4.1 mini 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-4.1 mini lists at $0.40 and $1.60.
Is GPT-4.1 mini or Trinity Large Thinking better for coding?
Trinity Large Thinking scores higher on coding benchmarks: 34.1 versus 30.6 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 mini does, with 1.05M tokens against 262K.
How many benchmarks do GPT-4.1 mini and Trinity Large Thinking share?
19 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and Trinity Large Thinking has 24.