Model comparison
Gemini 2.5 Flash-Lite vs Trinity Large Thinking
Trinity Large Thinking is the stronger model overall, scoring 38.1 to 36.4 on the Noometry Index. Gemini 2.5 Flash-Lite costs 2.2× less per token, which makes it the better buy when Trinity Large Thinking's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
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Arcee AISummary
- They share 18 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 5 categories and Trinity Large Thinking in 3 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Trinity Large Thinking leads 40.3 to 32.1.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.25 / $0.80 for Trinity Large Thinking.
- Gemini 2.5 Flash-Lite 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-Lite | Trinity Large Thinking | |
|---|---|---|
| Provider | Arcee AI | |
| Noometry Index | 36.4 | 38.1 |
| Released | 2025-06-17 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 66K | 80K |
| Input $ / M tokens | $0.10 | $0.25 |
| Output $ / M tokens | $0.40 | $0.80 |
| Results tracked | 33 | 24 |
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Category by category
Coding Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 38.0 (#167), Trinity Large Thinking: 33.8 (#238)
| Benchmark | Gemini 2.5 Flash-Lite | Trinity Large Thinking |
|---|---|---|
| LMArena Coding | 1373 | 1381 |
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |
| WeirdML | 35.2% | — |
| ALE-Bench | 325.9 | — |
Agentic & Tool Use Not comparable
Gemini 2.5 Flash-Lite: 27.8 (#89), Trinity Large Thinking: —
| Benchmark | Gemini 2.5 Flash-Lite | Trinity Large Thinking |
|---|---|---|
| Berkeley Function Calling Leaderboard | 36.9% | — |
Reasoning Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 21.5 (#196), Trinity Large Thinking: 16.3 (#298)
| Benchmark | Gemini 2.5 Flash-Lite | Trinity Large Thinking |
|---|---|---|
| LMArena Hard Prompts | 1377 | 1350 |
| Kagi LLM Benchmark | 40.5% | — |
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Thematic Generalization | — | 41.6% |
| DTBench | 62.8% | — |
| LMCA | 18.1% | — |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 133.93 | — |
Math Too close to call
Gemini 2.5 Flash-Lite: 35.5 (#144), Trinity Large Thinking: 34.9 (#149)
| Benchmark | Gemini 2.5 Flash-Lite | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1373 | 1366 |
| Omni-MATH | 48% | — |
Knowledge Trinity Large Thinking leads
Gemini 2.5 Flash-Lite: 32.1 (#206), Trinity Large Thinking: 40.3 (#107)
| Benchmark | Gemini 2.5 Flash-Lite | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | 3.3% | 6.9% |
| LMArena Expert | 1373 | 1359 |
| MMLU-Pro | 53.7% | — |
| GPQA (HELM) | 30.9% | — |
Multimodal Not comparable
Gemini 2.5 Flash-Lite: 28.6 (#109), Trinity Large Thinking: —
| Benchmark | Gemini 2.5 Flash-Lite | Trinity Large Thinking |
|---|---|---|
| LMArena Vision | 1198 | — |
| VPCT | 30% | — |
Multilingual Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 49.5 (#129), Trinity Large Thinking: 46.4 (#155)
| Benchmark | Gemini 2.5 Flash-Lite | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1369 | 1325 |
| LMArena Chinese | 1404 | 1372 |
| LMArena French | 1388 | 1374 |
| LMArena German | 1390 | 1356 |
| LMArena Japanese | 1359 | 1312 |
| LMArena Korean | 1358 | 1304 |
| LMArena Russian | 1373 | 1338 |
| LMArena Spanish | 1396 | 1356 |
Instruction Following Too close to call
Gemini 2.5 Flash-Lite: 70.2 (#163), Trinity Large Thinking: 70.7 (#157)
| Benchmark | Gemini 2.5 Flash-Lite | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1366 | 1334 |
| IFEval | 81% | — |
Long Context Trinity Large Thinking leads
Gemini 2.5 Flash-Lite: 33.3 (#257), Trinity Large Thinking: 41.2 (#139)
| Benchmark | Gemini 2.5 Flash-Lite | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1373 | 1355 |
| Fiction.LiveBench | 47.2% | — |
Writing & Preference Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 57.0 (#130), Trinity Large Thinking: 54.0 (#152)
| Benchmark | Gemini 2.5 Flash-Lite | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1379 | 1340 |
| LMArena Creative Writing | 1366 | 1321 |
| LMArena Multi-Turn | 1367 | 1342 |
| WildBench | 81.8% | — |
Frequently asked questions
Is Gemini 2.5 Flash-Lite better than Trinity Large Thinking?
Trinity Large Thinking is the stronger model overall, scoring 38.1 to 36.4 on the Noometry Index. Gemini 2.5 Flash-Lite costs 2.2× less per token, which makes it the better buy when Trinity Large Thinking's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash-Lite or Trinity Large Thinking?
Gemini 2.5 Flash-Lite is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Trinity Large Thinking lists at $0.25 and $0.80.
Is Gemini 2.5 Flash-Lite or Trinity Large Thinking better for coding?
Gemini 2.5 Flash-Lite scores higher on coding benchmarks: 38.0 versus 33.8 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Flash-Lite does, with 1.05M tokens against 262K.
How many benchmarks do Gemini 2.5 Flash-Lite and Trinity Large Thinking share?
18 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and Trinity Large Thinking has 24.