Trinity Large Thinking vs Gemini 3.7 Flash
Updated October 21, 2026. 45 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 45 shared
Decision reading
Pick Gemini 3.7 Flash for coding: it scores 69.9 on the Vibe Coding Index against 5.4 for Trinity Large Thinking.
Pick Trinity Large Thinking when output tokens cost 4.7x less.
Model ATrinity Large ThinkingArcee AI5.4/1001 independent benchmarkNo cost per solved taskModel BGemini 3.7 FlashGoogle69.9/1002 independent benchmarks$1.78 per solved task
- Shared results
- 45
- Trinity Large Thinking only
- 7
- Gemini 3.7 Flash only
- 67
- Like-for-like categories
- 7 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, four public coding benchmarks
Gemini 3.7 Flash
Gemini 3.7 Flash scores 69.9 against 5.4.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 39.6 against 10.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Trinity Large Thinking has a AA Agentic Index result, 1.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Gemini 3.7 Flash has a GPQA Diamond result, 93.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.7 Flash has a MMLU Pro result, 90.1%.
Directional only
Web design
Design Arena: websites
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 1304 against 1137.
Same board, both measured
Long documents
Listed context window
Gemini 3.7 Flash
Gemini 3.7 Flash takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Trinity Large Thinking
Trinity Large Thinking $0.0006, Gemini 3.7 Flash $0.0026 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.7 Flash has the number, $1.78.
Directional only
At a glance
- Coding index
- Trinity Large Thinking 5.4 from 1 benchmark, Gemini 3.7 Flash 69.9 from 2 benchmarks.
- Widest category
- Coding, 40.0 points apart on average over 7 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: Trinity Large Thinking 1231 against Gemini 3.7 Flash 1587, 59.4 points apart on a 0 to 100 scale.
- Output price
- Trinity Large Thinking $0.80 against Gemini 3.7 Flash $3.75 per million output tokens, 4.7x apart.
- Context window
- Trinity Large Thinking takes 262K tokens, Gemini 3.7 Flash 1.05M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Trinity Large Thinking | Bars | Gemini 3.7 Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 7 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 8 | ||
| General | 0 | 18 | ||
| All shared boards | 0 | 45 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index07
| Benchmark | Trinity Large Thinking | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 80.5% | Only Gemini 3.7 Flash measured |
| LMArena WebDev | 1238 | 1591 | Gemini 3.7 Flash |
| AA Coding Index | 25.8 | 71.5 | Gemini 3.7 Flash |
| LiveCodeBench (Vals AI) | Not measured | 88.7% | Only Gemini 3.7 Flash measured |
| SWE-bench Verified (Vals AI) | Not measured | 80.8% | Only Gemini 3.7 Flash measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 12.1% | Only Gemini 3.7 Flash measured |
| Vibe Code Bench (Vals AI) | Not measured | 70.4% | Only Gemini 3.7 Flash measured |
| Code migration (Vals AI) | Not measured | 34.8% | Only Gemini 3.7 Flash measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Gemini 3.7 Flash measured |
| IOI (Vals AI) | Not measured | 67.8% | Only Gemini 3.7 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 77.5% | Only Gemini 3.7 Flash measured |
| SkillsBench (Vals AI) | Not measured | 65.9% | Only Gemini 3.7 Flash measured |
| CyberBench (Vals AI) | Not measured | 43.8% | Only Gemini 3.7 Flash measured |
| SciCode | 40.6% | 59.8% | Gemini 3.7 Flash |
| Terminal-Bench Hard (Artificial Analysis run) | 22.7% | Not measured | Only Trinity Large Thinking measured |
| FrontierCode | Not measured | 43.6% | Only Gemini 3.7 Flash measured |
| FrontierSWE | Not measured | 20.3% | Only Gemini 3.7 Flash measured |
| ALE-Bench | Not measured | 904.3 | Only Gemini 3.7 Flash measured |
| LMArena Text: coding | 1357 | 1499 | Gemini 3.7 Flash |
| LMArena Text: software and IT | 1362 | 1498 | Gemini 3.7 Flash |
| LMArena WebDev: React | 1231 | 1587 | Gemini 3.7 Flash |
| LMArena WebDev: HTML | 1240 | 1593 | Gemini 3.7 Flash |
| LMArena WebDev: from an image | Not measured | 1599 | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Trinity Large Thinking | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 39.6 | Gemini 3.7 Flash |
| Epoch Capabilities Index | Not measured | 158.0 | Only Gemini 3.7 Flash measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
| Benchmark | Trinity Large Thinking | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: agents building web apps | Not measured | 1224 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building full-stack apps | Not measured | 1208 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building mobile apps | Not measured | 1230 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Android apps | Not measured | 1247 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Godot games | Not measured | 1264 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building games | Not measured | 1235 | Only Gemini 3.7 Flash measured |
| Design Arena: spreadsheets | Not measured | 1028 | Only Gemini 3.7 Flash measured |
| LiveBench research | Not measured | 76.5% | Only Gemini 3.7 Flash measured |
| LiveBench browser | Not measured | 56.0% | Only Gemini 3.7 Flash measured |
| LiveBench long agentic | Not measured | 28.3% | Only Gemini 3.7 Flash measured |
| SREBench (Vals AI) | Not measured | 4.6% | Only Gemini 3.7 Flash measured |
| Finance Agent (Vals AI) | Not measured | 59.0% | Only Gemini 3.7 Flash measured |
| Tax Agent Bench (Vals AI) | Not measured | 22.8% | Only Gemini 3.7 Flash measured |
| Legal Research Bench (Vals AI) | Not measured | 34.6% | Only Gemini 3.7 Flash measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 71.3% | Only Gemini 3.7 Flash measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 7.1% | Only Gemini 3.7 Flash measured |
| τ²-Bench Telecom | 90.1% | Not measured | Only Trinity Large Thinking measured |
| APEX-Agents | Not measured | 67.8% | Only Gemini 3.7 Flash measured |
| Remote Labor Index | Not measured | 5.0% | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 19 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Trinity Large Thinking | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 93.9% | Only Gemini 3.7 Flash measured |
| LiveBench reasoning | Not measured | 87.8% | Only Gemini 3.7 Flash measured |
| MMMU Pro (Vals AI) | Not measured | 89.0% | Only Gemini 3.7 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 75.2% | 94.5% | Gemini 3.7 Flash |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | 47.9% | Gemini 3.7 Flash |
| GPQA Diamond (Epoch AI run) | Not measured | 94.8% | Only Gemini 3.7 Flash measured |
| ARC-AGI | Not measured | 95.5% | Only Gemini 3.7 Flash measured |
| ARC-AGI-2 | Not measured | 84.6% | Only Gemini 3.7 Flash measured |
| Chess puzzles | Not measured | 66.0% | Only Gemini 3.7 Flash measured |
| Mystery game puzzles | Not measured | 37.0% | Only Gemini 3.7 Flash measured |
| LMArena Text: hard prompts | 1342 | 1495 | Gemini 3.7 Flash |
| LMArena Text: expert | 1359 | 1512 | Gemini 3.7 Flash |
| LMArena Text: hard prompts in English | 1356 | 1487 | Gemini 3.7 Flash |
| LMArena Vision: diagrams | Not measured | 1329 | Only Gemini 3.7 Flash measured |
| LMArena Vision: homework | Not measured | 1320 | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Trinity Large Thinking | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 97.2% | Only Gemini 3.7 Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 71.6% | Only Gemini 3.7 Flash measured |
| FrontierMath, tier 4 | Not measured | 36.6% | Only Gemini 3.7 Flash measured |
| ProofBench | Not measured | 58.0% | Only Gemini 3.7 Flash measured |
| LMArena Text: math | 1365 | 1511 | Gemini 3.7 Flash |
| LMArena Text: mathematical work | 1350 | 1502 | Gemini 3.7 Flash |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Trinity Large Thinking | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 90.1% | Only Gemini 3.7 Flash measured |
| LegalBench (Vals AI) | Not measured | 87.3% | Only Gemini 3.7 Flash measured |
| CaseLaw (Vals AI) | 57.9% | Not measured | Only Trinity Large Thinking measured |
| CorpFin (Vals AI) | 54.7% | Not measured | Only Trinity Large Thinking measured |
| TaxEval (Vals AI) | Not measured | 74.7% | Only Gemini 3.7 Flash measured |
| MortgageTax (Vals AI) | Not measured | 66.7% | Only Gemini 3.7 Flash measured |
| MedCode (Vals AI) | Not measured | 53.4% | Only Gemini 3.7 Flash measured |
| SimpleQA Verified | Not measured | 69.2% | Only Gemini 3.7 Flash measured |
| LMArena Text: science | 1355 | 1511 | Gemini 3.7 Flash |
| LMArena Text: medicine and healthcare | 1349 | 1494 | Gemini 3.7 Flash |
| LMArena Text: legal and government | 1345 | 1496 | Gemini 3.7 Flash |
| LMArena Text: business and finance | 1329 | 1479 | Gemini 3.7 Flash |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | Trinity Large Thinking | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1137 | 1304 | Gemini 3.7 Flash |
| Design Arena: UI components | 1045 | 1299 | Gemini 3.7 Flash |
| Design Arena: game dev | 1079 | 1318 | Gemini 3.7 Flash |
| Design Arena: data viz | 1098 | 1315 | Gemini 3.7 Flash |
| Design Arena: 3D | 1082 | 1308 | Gemini 3.7 Flash |
| Design Arena: all code categories | 1117 | 1308 | Gemini 3.7 Flash |
| Design Arena: SVG | 1016 | 1283 | Gemini 3.7 Flash |
| Design Arena: ASCII art | 1041 | 1276 | Gemini 3.7 Flash |
| LiveBench design | Not measured | 73.2% | Only Gemini 3.7 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
| Benchmark | Trinity Large Thinking | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 68.0% | Only Gemini 3.7 Flash measured |
| SAGE (Vals AI) | Not measured | 49.2% | Only Gemini 3.7 Flash measured |
| MedScribe (Vals AI) | Not measured | 83.9% | Only Gemini 3.7 Flash measured |
| IFBench | 56.3% | Not measured | Only Trinity Large Thinking measured |
| Long context reasoning (AA-LCR) | 38.0% | 83.0% | Gemini 3.7 Flash |
| DTBench | Not measured | 96.8% | Only Gemini 3.7 Flash measured |
| LMCA | Not measured | 50.4% | Only Gemini 3.7 Flash measured |
| Surface Evolver Bench | 15.6% | Not measured | Only Trinity Large Thinking measured |
| Furniture assembly | Not measured | 26.7% | Only Gemini 3.7 Flash measured |
| LMArena Text | 1340 | 1489 | Gemini 3.7 Flash |
| LMArena Text: instruction following | 1326 | 1484 | Gemini 3.7 Flash |
| LMArena Text: creative writing | 1308 | 1488 | Gemini 3.7 Flash |
| LMArena Vision | Not measured | 1314 | Only Gemini 3.7 Flash measured |
| LMArena Text: English | 1356 | 1483 | Gemini 3.7 Flash |
| LMArena Text: non-English | 1325 | 1487 | Gemini 3.7 Flash |
| LMArena Text: Chinese | 1371 | 1552 | Gemini 3.7 Flash |
| LMArena Text: German | 1356 | 1506 | Gemini 3.7 Flash |
| LMArena Text: Japanese | 1312 | 1511 | Gemini 3.7 Flash |
| LMArena Text: Korean | 1306 | 1481 | Gemini 3.7 Flash |
| LMArena Text: French | 1366 | 1500 | Gemini 3.7 Flash |
| LMArena Text: Spanish | 1327 | 1495 | Gemini 3.7 Flash |
| LMArena Text: Russian | 1338 | 1515 | Gemini 3.7 Flash |
| LMArena Text: Polish | 1312 | 1503 | Gemini 3.7 Flash |
| LMArena Text: multi-turn | 1320 | 1485 | Gemini 3.7 Flash |
| LMArena Text: longer queries | 1318 | 1492 | Gemini 3.7 Flash |
| LMArena Text: writing and language | 1317 | 1491 | Gemini 3.7 Flash |
| LMArena Text: entertainment and media | 1296 | 1477 | Gemini 3.7 Flash |
| LMArena Vision: English | Not measured | 1309 | Only Gemini 3.7 Flash measured |
| LMArena Vision: Chinese | Not measured | 1394 | Only Gemini 3.7 Flash measured |
| LMArena Vision: reading text | Not measured | 1322 | Only Gemini 3.7 Flash measured |
| LMArena Vision: humor | Not measured | 1299 | Only Gemini 3.7 Flash measured |
| LMArena Vision: creative writing | Not measured | 1312 | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Trinity Large Thinking | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Trinity Large Thinking$0.0006Fits in one request
Gemini 3.7 Flash$0.0026Fits in one request
Trinity Large Thinking costs less
Repository review
50K input + 3K output tokens
Trinity Large Thinking$0.015Fits in one request
Gemini 3.7 Flash$0.049Fits in one request
Trinity Large Thinking costs less
Agent loop
200K input + 10K output tokens
Trinity Large Thinking$0.058Fits in one request
Gemini 3.7 Flash$0.188Fits in one request
Trinity Large Thinking costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Arcee AI Trinity Large Thinking | Google Gemini 3.7 Flash |
|---|---|---|
| Maker | Arcee AI | |
| Weights | Open weights | No public weights listed |
| Released | April 1, 2026 | August 13, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.25 | $0.75 |
| Output $/Mtok | $0.80 | $3.75 |
| Coding index | 5.4 | 69.9 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | $1.78 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Trinity Large Thinking better than Gemini 3.7 Flash for coding?
Pick Gemini 3.7 Flash for coding: it scores 69.9 on the Vibe Coding Index against 5.4 for Trinity Large Thinking. Pick Trinity Large Thinking when output tokens cost 4.7x less.
Which is cheaper, Trinity Large Thinking or Gemini 3.7 Flash?
Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; Gemini 3.7 Flash costs $0.75 and $3.75. Cost per solved task is known for Gemini 3.7 Flash only.
Which has the bigger context window, Trinity Large Thinking or Gemini 3.7 Flash?
Gemini 3.7 Flash, with 1.05M tokens against 262K.
How many benchmarks is the Trinity Large Thinking vs Gemini 3.7 Flash comparison based on?
45 benchmarks have a result for both models as of October 21, 2026. Trinity Large Thinking's coding index rests on 1 independent benchmark and Gemini 3.7 Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.