Trinity Large Thinking vs Gemma 4 26B A4B
Updated October 21, 2026. 37 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Gemma 4 26B A4B for coding: it scores 22.8 on the Vibe Coding Index against 5.4 for Trinity Large Thinking.
Pick Trinity Large Thinking when what matters is SciCode or τ²-Bench Telecom, where it leads.
- Shared results
- 37
- Trinity Large Thinking only
- 15
- Gemma 4 26B A4B only
- 17
- 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
Gemma 4 26B A4B
Gemma 4 26B A4B scores 22.8 against 5.4.
One benchmark behind each score
Intelligence
AA Intelligence Index
Gemma 4 26B A4B
Gemma 4 26B A4B leads, 16.7 against 10.8.
Same board, both measured
Agentic work
AA Agentic Index
Gemma 4 26B A4B
Gemma 4 26B A4B leads, 2.9 against 1.0.
Same board, both measured
Web design
Design Arena: websites
No call
Only Trinity Large Thinking has a Design Arena: websites result, 1137.
Directional only
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 26B A4B
Trinity Large Thinking $0.0006, Gemma 4 26B A4B $0.0002 per turn.
List prices
At a glance
- Coding index
- Trinity Large Thinking 5.4 from 1 benchmark, Gemma 4 26B A4B 22.8 from 1 benchmark.
- Widest category
- Agentic work, 24.2 points apart on average over 2 shared benchmarks.
- Widest single gap
- τ²-Bench Telecom: Trinity Large Thinking 90.1% against Gemma 4 26B A4B 43.6%, 46.5 points apart on a 0 to 100 scale.
- Output price
- Trinity Large Thinking $0.80 against Gemma 4 26B A4B $0.255 per million output tokens, 3.1x apart.
- Context window
- Both take 262K tokens.
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 | Gemma 4 26B A4B | Ties |
|---|---|---|---|---|
| Coding | 1 | 7 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 1 | 1 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 15 | ||
| All shared boards | 2 | 35 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index17
| Benchmark | Trinity Large Thinking | Gemma 4 26B A4B | Leader |
|---|---|---|---|
| LMArena WebDev | 1238 | 1360 | Gemma 4 26B A4B |
| AA Coding Index | 25.8 | 39.3 | Gemma 4 26B A4B |
| SciCode | 40.6% | 40.0% | Trinity Large Thinking |
| Terminal-Bench Hard (Artificial Analysis run) | 22.7% | 25.0% | Gemma 4 26B A4B |
| WeirdML | Not measured | 35.2% | Only Gemma 4 26B A4B measured |
| ALE-Bench | Not measured | 927.2 | Only Gemma 4 26B A4B measured |
| LMArena Text: coding | 1357 | 1446 | Gemma 4 26B A4B |
| LMArena Text: software and IT | 1362 | 1454 | Gemma 4 26B A4B |
| LMArena WebDev: React | 1231 | 1351 | Gemma 4 26B A4B |
| LMArena WebDev: HTML | 1240 | 1362 | Gemma 4 26B A4B |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Trinity Large Thinking | Gemma 4 26B A4B | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 16.7 | Gemma 4 26B A4B |
| Epoch Capabilities Index | Not measured | 141.9 | Only Gemma 4 26B A4B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Trinity Large Thinking | Gemma 4 26B A4B | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | 2.9 | Gemma 4 26B A4B |
| τ²-Bench Telecom | 90.1% | 43.6% | Trinity Large Thinking |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Trinity Large Thinking | Gemma 4 26B A4B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 75.2% | 79.2% | Gemma 4 26B A4B |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | 19.3% | Gemma 4 26B A4B |
| GPQA Diamond (Epoch AI run) | Not measured | 73.2% | Only Gemma 4 26B A4B measured |
| LMArena Text: hard prompts | 1342 | 1438 | Gemma 4 26B A4B |
| LMArena Text: expert | 1359 | 1447 | Gemma 4 26B A4B |
| LMArena Text: hard prompts in English | 1356 | 1448 | Gemma 4 26B A4B |
| LMArena Vision: diagrams | Not measured | 1264 | Only Gemma 4 26B A4B measured |
| LMArena Vision: homework | Not measured | 1293 | Only Gemma 4 26B A4B measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Trinity Large Thinking | Gemma 4 26B A4B | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 82.2% | Only Gemma 4 26B A4B measured |
| LMArena Text: math | 1365 | 1470 | Gemma 4 26B A4B |
| LMArena Text: mathematical work | 1350 | 1475 | Gemma 4 26B A4B |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Trinity Large Thinking | Gemma 4 26B A4B | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 57.9% | Not measured | Only Trinity Large Thinking measured |
| CorpFin (Vals AI) | 54.7% | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: science | 1355 | 1446 | Gemma 4 26B A4B |
| LMArena Text: medicine and healthcare | 1349 | 1428 | Gemma 4 26B A4B |
| LMArena Text: legal and government | 1345 | 1457 | Gemma 4 26B A4B |
| LMArena Text: business and finance | 1329 | 1429 | Gemma 4 26B A4B |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Trinity Large Thinking | Gemma 4 26B A4B | Leader |
|---|---|---|---|
| Design Arena: websites | 1137 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: UI components | 1045 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: game dev | 1079 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: data viz | 1098 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: 3D | 1082 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: all code categories | 1117 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: SVG | 1016 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: ASCII art | 1041 | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index015
| Benchmark | Trinity Large Thinking | Gemma 4 26B A4B | Leader |
|---|---|---|---|
| IFBench | 56.3% | 72.4% | Gemma 4 26B A4B |
| Long context reasoning (AA-LCR) | 38.0% | 65.7% | Gemma 4 26B A4B |
| DTBench | Not measured | 74.9% | Only Gemma 4 26B A4B measured |
| LMCA | Not measured | 29.7% | Only Gemma 4 26B A4B measured |
| Surface Evolver Bench | 15.6% | Not measured | Only Trinity Large Thinking measured |
| LMArena Text | 1340 | 1434 | Gemma 4 26B A4B |
| LMArena Text: instruction following | 1326 | 1420 | Gemma 4 26B A4B |
| LMArena Text: creative writing | 1308 | 1400 | Gemma 4 26B A4B |
| LMArena Vision | Not measured | 1260 | Only Gemma 4 26B A4B measured |
| LMArena Text: English | 1356 | 1444 | Gemma 4 26B A4B |
| LMArena Text: non-English | 1325 | 1421 | Gemma 4 26B A4B |
| LMArena Text: Chinese | 1371 | 1495 | Gemma 4 26B A4B |
| LMArena Text: German | 1356 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: Japanese | 1312 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: Korean | 1306 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: French | 1366 | 1460 | Gemma 4 26B A4B |
| LMArena Text: Spanish | 1327 | 1415 | Gemma 4 26B A4B |
| LMArena Text: Russian | 1338 | 1434 | Gemma 4 26B A4B |
| LMArena Text: Polish | 1312 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: multi-turn | 1320 | 1441 | Gemma 4 26B A4B |
| LMArena Text: longer queries | 1318 | 1427 | Gemma 4 26B A4B |
| LMArena Text: writing and language | 1317 | 1405 | Gemma 4 26B A4B |
| LMArena Text: entertainment and media | 1296 | 1403 | Gemma 4 26B A4B |
| LMArena Vision: English | Not measured | 1256 | Only Gemma 4 26B A4B measured |
| LMArena Vision: Chinese | Not measured | 1312 | Only Gemma 4 26B A4B measured |
| LMArena Vision: reading text | Not measured | 1268 | Only Gemma 4 26B A4B measured |
| LMArena Vision: humor | Not measured | 1272 | Only Gemma 4 26B A4B measured |
| LMArena Vision: captioning | Not measured | 1297 | Only Gemma 4 26B A4B measured |
| LMArena Vision: recognizing things | Not measured | 1191 | Only Gemma 4 26B A4B measured |
| LMArena Vision: creative writing | Not measured | 1256 | Only Gemma 4 26B A4B measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Trinity Large Thinking | Gemma 4 26B A4B | 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
Gemma 4 26B A4B costs less
Repository review
50K input + 3K output tokens
Gemma 4 26B A4B costs less
Agent loop
200K input + 10K output tokens
Gemma 4 26B A4B 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 Gemma 4 26B A4B |
|---|---|---|
| Maker | Arcee AI | |
| Weights | Open weights | Open weights |
| Released | April 1, 2026 | April 3, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.25 | $0.0765 |
| Output $/Mtok | $0.80 | $0.255 |
| Coding index | 5.4 | 22.8 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Trinity Large Thinking better than Gemma 4 26B A4B for coding?
Pick Gemma 4 26B A4B for coding: it scores 22.8 on the Vibe Coding Index against 5.4 for Trinity Large Thinking. Pick Trinity Large Thinking when what matters is SciCode or τ²-Bench Telecom, where it leads.
Which is cheaper, Trinity Large Thinking or Gemma 4 26B A4B?
Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; Gemma 4 26B A4B costs $0.0765 and $0.255. Cost per solved task is known for neither of them.
Which has the bigger context window, Trinity Large Thinking or Gemma 4 26B A4B?
Neither: both take 262K tokens.
How many benchmarks is the Trinity Large Thinking vs Gemma 4 26B A4B comparison based on?
37 benchmarks have a result for both models as of October 21, 2026. Trinity Large Thinking's coding index rests on 1 independent benchmark and Gemma 4 26B A4B's on 1. Where only one model has a result, the page says so instead of naming a winner.