Trinity Large Thinking vs Llama 4 Scout
Trinity Large Thinking leads Llama 4 Scout on the Artificial Analysis Intelligence Index, 10.8 to 6.5, and Llama 4 Scout costs 1.6x less per output token ($0.50 vs $0.80 per million). Updated October 21, 2026; 44 benchmarks have a result for both.
Trinity Large Thinking or Llama 4 Scout: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 44
- Trinity Large Thinking only
- 8
- Llama 4 Scout only
- 38
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Trinity Large Thinking
Trinity Large Thinking leads, 10.8 against 6.5.
Same board, both measured
Agentic work
AA Agentic Index
Trinity Large Thinking
Trinity Large Thinking leads, 1.0 against 0.5.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Llama 4 Scout has a GPQA Diamond result, 47.0%.
Directional only
Math
AIME
No call
Only Llama 4 Scout has a AIME result, 19.0%.
Directional only
Knowledge
MMLU Pro
No call
Only Llama 4 Scout has a MMLU Pro result, 69.6%.
Directional only
Web design
Design Arena: websites
Trinity Large Thinking
Trinity Large Thinking leads, 1137 against 750.
Same board, both measured
Long documents
Listed context window
Llama 4 Scout
Llama 4 Scout takes 1.31M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 4 Scout
Trinity Large Thinking $0.0006, Llama 4 Scout $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Llama 4 Scout has the number, $1.276.
Directional only
At a glance
- Coding index
- Trinity Large Thinking not benchmarked, Llama 4 Scout not benchmarked.
- Widest category
- Agentic work, 37.5 points apart on average over 2 shared benchmarks.
- Widest single gap
- τ²-Bench Telecom: Trinity Large Thinking 90.1% against Llama 4 Scout 15.5%, 74.6 points apart on a 0 to 100 scale.
- Output price
- Trinity Large Thinking $0.80 against Llama 4 Scout $0.50 per million output tokens, 1.6x apart.
- Context window
- Trinity Large Thinking takes 262K tokens, Llama 4 Scout 1.31M.
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 | Llama 4 Scout | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 5 | 0 | ||
| Web design | 5 | 0 | ||
| General | 19 | 0 | ||
| All shared boards | 44 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
| Benchmark | Trinity Large Thinking | Llama 4 Scout | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 9.1% | Only Llama 4 Scout measured |
| LMArena WebDev | 1238 | Not measured | Only Trinity Large Thinking measured |
| AA Coding Index | 25.8 | 8.2 | Trinity Large Thinking |
| LiveCodeBench (Vals AI) | Not measured | 38.5% | Only Llama 4 Scout measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 29.9% | Only Llama 4 Scout measured |
| SciCode | 40.6% | 21.3% | Trinity Large Thinking |
| Terminal-Bench Hard (Artificial Analysis run) | 22.7% | 1.5% | Trinity Large Thinking |
| LMArena Text: coding | 1357 | 1286 | Trinity Large Thinking |
| LMArena Text: software and IT | 1362 | 1286 | Trinity Large Thinking |
| LMArena WebDev: React | 1231 | Not measured | Only Trinity Large Thinking measured |
| LMArena WebDev: HTML | 1240 | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Trinity Large Thinking | Llama 4 Scout | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 6.5 | Trinity Large Thinking |
| Epoch Capabilities Index | Not measured | 129.6 | Only Llama 4 Scout measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Trinity Large Thinking | Llama 4 Scout | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | 0.5 | Trinity Large Thinking |
| τ²-Bench Telecom | 90.1% | 15.5% | Trinity Large Thinking |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 28.1% | Only Llama 4 Scout measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Trinity Large Thinking | Llama 4 Scout | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 47.0% | Only Llama 4 Scout measured |
| MMMU Pro (Vals AI) | Not measured | 58.8% | Only Llama 4 Scout measured |
| GPQA Diamond (Artificial Analysis run) | 75.2% | 58.7% | Trinity Large Thinking |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | 3.8% | Trinity Large Thinking |
| GPQA Diamond (Epoch AI run) | Not measured | 51.8% | Only Llama 4 Scout measured |
| ARC-AGI | Not measured | 0.5% | Only Llama 4 Scout measured |
| ARC-AGI-2 | Not measured | 0.0% | Only Llama 4 Scout measured |
| LMArena Text: hard prompts | 1342 | 1266 | Trinity Large Thinking |
| LMArena Text: expert | 1359 | 1235 | Trinity Large Thinking |
| LMArena Text: hard prompts in English | 1356 | 1293 | Trinity Large Thinking |
| LMArena Vision: diagrams | Not measured | 1125 | Only Llama 4 Scout measured |
| LMArena Vision: homework | Not measured | 1148 | Only Llama 4 Scout measured |
| Kagi LLM Benchmark | Not measured | 36.9% | Only Llama 4 Scout measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Trinity Large Thinking | Llama 4 Scout | Leader |
|---|---|---|---|
| AIME | Not measured | 19.0% | Only Llama 4 Scout measured |
| MATH 500 (Vals AI) | Not measured | 79.2% | Only Llama 4 Scout measured |
| MGSM (Vals AI) | Not measured | 88.0% | Only Llama 4 Scout measured |
| AA Math Index | Not measured | 14.0 | Only Llama 4 Scout measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 14.0% | Only Llama 4 Scout measured |
| OTIS Mock AIME | Not measured | 7.8% | Only Llama 4 Scout measured |
| MATH level 5 | Not measured | 62.3% | Only Llama 4 Scout measured |
| LMArena Text: math | 1365 | 1287 | Trinity Large Thinking |
| LMArena Text: mathematical work | 1350 | 1286 | Trinity Large Thinking |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Trinity Large Thinking | Llama 4 Scout | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 69.6% | Only Llama 4 Scout measured |
| LegalBench (Vals AI) | Not measured | 72.0% | Only Llama 4 Scout measured |
| CaseLaw (Vals AI) | 57.9% | Not measured | Only Trinity Large Thinking measured |
| CorpFin (Vals AI) | 54.7% | 46.8% | Trinity Large Thinking |
| TaxEval (Vals AI) | Not measured | 55.2% | Only Llama 4 Scout measured |
| MortgageTax (Vals AI) | Not measured | 57.8% | Only Llama 4 Scout measured |
| MedQA (Vals AI) | Not measured | 50.9% | Only Llama 4 Scout measured |
| MedCode (Vals AI) | Not measured | 23.3% | Only Llama 4 Scout measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 75.2% | Only Llama 4 Scout measured |
| LMArena Text: science | 1355 | 1278 | Trinity Large Thinking |
| LMArena Text: medicine and healthcare | 1349 | 1275 | Trinity Large Thinking |
| LMArena Text: legal and government | 1345 | 1285 | Trinity Large Thinking |
| LMArena Text: business and finance | 1329 | 1257 | Trinity Large Thinking |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Trinity Large Thinking | Llama 4 Scout | Leader |
|---|---|---|---|
| Design Arena: websites | 1137 | 750 | Trinity Large Thinking |
| Design Arena: UI components | 1045 | 768 | Trinity Large Thinking |
| Design Arena: game dev | 1079 | 773 | Trinity Large Thinking |
| Design Arena: data viz | 1098 | 896 | Trinity Large Thinking |
| Design Arena: 3D | 1082 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: all code categories | 1117 | 790 | Trinity Large Thinking |
| Design Arena: SVG | 1017 | 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 index190
| Benchmark | Trinity Large Thinking | Llama 4 Scout | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 34.8% | Only Llama 4 Scout measured |
| MedScribe (Vals AI) | Not measured | 50.6% | Only Llama 4 Scout measured |
| IFBench | 56.3% | 39.5% | Trinity Large Thinking |
| Long context reasoning (AA-LCR) | 38.0% | 27.7% | Trinity Large Thinking |
| DTBench | Not measured | 57.9% | Only Llama 4 Scout measured |
| LMCA | Not measured | 12.0% | Only Llama 4 Scout measured |
| Fiction.LiveBench | Not measured | 36.0% | Only Llama 4 Scout measured |
| Surface Evolver Bench | 15.6% | Not measured | Only Trinity Large Thinking measured |
| LMArena Text | 1340 | 1279 | Trinity Large Thinking |
| LMArena Text: instruction following | 1326 | 1248 | Trinity Large Thinking |
| LMArena Text: creative writing | 1308 | 1249 | Trinity Large Thinking |
| LMArena Vision | Not measured | 1118 | Only Llama 4 Scout measured |
| LMArena Text: English | 1356 | 1304 | Trinity Large Thinking |
| LMArena Text: non-English | 1325 | 1252 | Trinity Large Thinking |
| LMArena Text: Chinese | 1371 | 1255 | Trinity Large Thinking |
| LMArena Text: German | 1356 | 1273 | Trinity Large Thinking |
| LMArena Text: Japanese | 1312 | 1206 | Trinity Large Thinking |
| LMArena Text: Korean | 1306 | 1207 | Trinity Large Thinking |
| LMArena Text: French | 1366 | 1283 | Trinity Large Thinking |
| LMArena Text: Spanish | 1327 | 1278 | Trinity Large Thinking |
| LMArena Text: Russian | 1338 | 1263 | Trinity Large Thinking |
| LMArena Text: Polish | 1312 | 1265 | Trinity Large Thinking |
| LMArena Text: multi-turn | 1320 | 1280 | Trinity Large Thinking |
| LMArena Text: longer queries | 1318 | 1265 | Trinity Large Thinking |
| LMArena Text: writing and language | 1317 | 1269 | Trinity Large Thinking |
| LMArena Text: entertainment and media | 1296 | 1242 | Trinity Large Thinking |
| LMArena Vision: English | Not measured | 1143 | Only Llama 4 Scout measured |
| LMArena Vision: Chinese | Not measured | 1106 | Only Llama 4 Scout measured |
| LMArena Vision: reading text | Not measured | 1117 | Only Llama 4 Scout measured |
| LMArena Vision: humor | Not measured | 1102 | Only Llama 4 Scout measured |
| LMArena Vision: creative writing | Not measured | 1126 | Only Llama 4 Scout measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Trinity Large Thinking | Llama 4 Scout | 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
Llama 4 Scout costs less
Repository review
50K input + 3K output tokens
Llama 4 Scout costs less
Agent loop
200K input + 10K output tokens
Llama 4 Scout 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 | Meta Llama 4 Scout |
|---|---|---|
| Maker | Arcee AI | Meta Llama |
| Weights | Open weights | Open weights |
| Released | April 1, 2026 | April 5, 2025 |
| Context window | 262K | 1.31M |
| Input $/Mtok | $0.25 | $0.175 |
| Output $/Mtok | $0.80 | $0.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | $1.276 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Trinity Large Thinking better than Llama 4 Scout for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Trinity Large Thinking or Llama 4 Scout?
Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; Llama 4 Scout costs $0.175 and $0.50. Cost per solved task is known for Llama 4 Scout only.
Which has the bigger context window, Trinity Large Thinking or Llama 4 Scout?
Llama 4 Scout, with 1.31M tokens against 262K.
How many benchmarks is the Trinity Large Thinking vs Llama 4 Scout comparison based on?
44 benchmarks have a result for both models as of October 21, 2026. Trinity Large Thinking's coding index rests on 1 independent benchmark and Llama 4 Scout's on 0. Where only one model has a result, the page says so instead of naming a winner.