Model comparison
Gemini 2.5 Flash vs Trinity Large Thinking
Gemini 2.5 Flash and Trinity Large Thinking score almost the same on the Noometry Index (39.3 vs 38.6), so choose on price, context window or the category you care about most.
Last verified . 19 shared benchmarks.
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Arcee AISummary
- They share 19 benchmarks with published results for both. Gemini 2.5 Flash scores higher in 7 categories and Trinity Large Thinking in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in long context, where Gemini 2.5 Flash leads 47.5 to 41.3.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $0.30 / $2.50 for Gemini 2.5 Flash.
- Gemini 2.5 Flash accepts more context: 1.05M tokens versus 262K.
- Trinity Large Thinking has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Flash | Trinity Large Thinking | |
|---|---|---|
| Provider | Arcee AI | |
| Noometry Index | 39.3 | 38.6 |
| Released | 2025-04-17 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 66K | 80K |
| Input $ / M tokens | $0.30 | $0.25 |
| Output $ / M tokens | $2.50 | $0.80 |
| Results tracked | 54 | 24 |
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Category by category
Coding Gemini 2.5 Flash leads
Gemini 2.5 Flash: 35.8 (#220), Trinity Large Thinking: 34.1 (#244)
| Benchmark | Gemini 2.5 Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Coding | 1424 | 1381 |
| SWE-bench Verified (bash only) | 28.7% | — |
| Aider Polyglot | 55.1% | — |
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |
| WeirdML | 41.9% | — |
| ALE-Bench | 661.88 | — |
Agentic & Tool Use Not comparable
Gemini 2.5 Flash: 30.8 (#74), Trinity Large Thinking: —
| Benchmark | Gemini 2.5 Flash | Trinity Large Thinking |
|---|---|---|
| Terminal-Bench | 17.1% | — |
| Berkeley Function Calling Leaderboard | 56.2% | — |
| TheAgentCompany | 41.1% | — |
| BALROG | 33.5% | — |
| Vending-Bench 2 | 548.84 | — |
Reasoning Gemini 2.5 Flash leads
Gemini 2.5 Flash: 18.1 (#286), Trinity Large Thinking: 16.9 (#298)
| Benchmark | Gemini 2.5 Flash | Trinity Large Thinking |
|---|---|---|
| CritPt | 1.1% | 0.9% |
| LMArena Hard Prompts | 1422 | 1350 |
| ARC-AGI-2 | 2.5% | — |
| SimpleBench | 41.2% | — |
| Kagi LLM Benchmark | 56.8% | — |
| NYT Connections (extended) | — | 16.5% |
| ARC-AGI-1 | 33.3% | — |
| EnigmaEval | 2.7% | — |
| Thematic Generalization | — | 41.6% |
| DTBench | 76.5% | — |
| LMCA | 27.5% | — |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 143.03 | — |
| ForecastBench | 60.6 | — |
Math Gemini 2.5 Flash leads
Gemini 2.5 Flash: 39.9 (#98), Trinity Large Thinking: 37.6 (#149)
| Benchmark | Gemini 2.5 Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1415 | 1366 |
| OTIS Mock AIME 2024-2025 | 73.1% | — |
| Omni-MATH | 38.5% | — |
| FrontierMath (Feb 2025 set) | 4.8% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Trinity Large Thinking leads
Gemini 2.5 Flash: 36.4 (#168), Trinity Large Thinking: 40.9 (#113)
| Benchmark | Gemini 2.5 Flash | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | 7.8% | 6.9% |
| LMArena Expert | 1426 | 1360 |
| Humanity's Last Exam | 12.1% | — |
| MMLU-Pro | 63.9% | — |
| Confabulations | 16.8% | — |
| GPQA (HELM) | 39% | — |
Multimodal Not comparable
Gemini 2.5 Flash: 41.8 (#32), Trinity Large Thinking: —
| Benchmark | Gemini 2.5 Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Vision | 1253 | — |
| GeoBench | 76% | — |
| VPCT | 46.2% | — |
| SpatialViz-Bench | 36.9% | — |
Multilingual Gemini 2.5 Flash leads
Gemini 2.5 Flash: 52.3 (#88), Trinity Large Thinking: 46.2 (#160)
| Benchmark | Gemini 2.5 Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1409 | 1325 |
| LMArena Chinese | 1450 | 1373 |
| LMArena French | 1433 | 1374 |
| LMArena German | 1418 | 1356 |
| LMArena Japanese | 1405 | 1311 |
| LMArena Korean | 1385 | 1306 |
| LMArena Russian | 1415 | 1337 |
| LMArena Spanish | 1421 | 1357 |
Instruction Following Gemini 2.5 Flash leads
Gemini 2.5 Flash: 75.7 (#54), Trinity Large Thinking: 70.5 (#162)
| Benchmark | Gemini 2.5 Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1405 | 1334 |
| IFEval | 89.8% | — |
Long Context Gemini 2.5 Flash leads
Gemini 2.5 Flash: 47.5 (#17), Trinity Large Thinking: 41.3 (#144)
| Benchmark | Gemini 2.5 Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1419 | 1355 |
| Fiction.LiveBench | 77.8% | — |
Writing & Preference Too close to call
Gemini 2.5 Flash: 53.8 (#157), Trinity Large Thinking: 53.8 (#158)
| Benchmark | Gemini 2.5 Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1417 | 1340 |
| LMArena Creative Writing | 1400 | 1320 |
| LMArena Multi-Turn | 1408 | 1342 |
| Short-Story Creative Writing | 76.5% | — |
| EQ-Bench Creative Writing | 1137 | — |
| WildBench | 81.7% | — |
Frequently asked questions
Is Gemini 2.5 Flash better than Trinity Large Thinking?
Gemini 2.5 Flash and Trinity Large Thinking score almost the same on the Noometry Index (39.3 vs 38.6), so choose on price, context window or the category you care about most.
Which is cheaper, Gemini 2.5 Flash 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; Gemini 2.5 Flash lists at $0.30 and $2.50.
Is Gemini 2.5 Flash or Trinity Large Thinking better for coding?
Gemini 2.5 Flash scores higher on coding benchmarks: 35.8 versus 34.1 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Flash does, with 1.05M tokens against 262K.
How many benchmarks do Gemini 2.5 Flash and Trinity Large Thinking share?
19 benchmarks have published results for both models. Gemini 2.5 Flash has 54 scored results on Noometry and Trinity Large Thinking has 24.