Trinity Large Thinking vs Qwen3.5 397B A17B
Qwen3.5 397B A17B leads Trinity Large Thinking on the Artificial Analysis Intelligence Index, 21.4 to 10.8, and Trinity Large Thinking costs 2.9x less per output token ($0.80 vs $2.34 per million). Updated October 21, 2026; 46 benchmarks have a result for both.
Trinity Large Thinking or Qwen3.5 397B A17B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Trinity Large Thinking for output tokens 2.9x cheaper ($0.80 vs $2.34 per million) and work measured by LMArena WebDev or SciCode, where it leads.
- Shared results
- 46
- Trinity Large Thinking only
- 6
- Qwen3.5 397B A17B only
- 19
- 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
Qwen3.5 397B A17B
Qwen3.5 397B A17B leads, 21.4 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
Web design
Design Arena: websites
Qwen3.5 397B A17B
Qwen3.5 397B A17B leads, 1191 against 1137.
Same board, both measured
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Trinity Large Thinking
Trinity Large Thinking $0.0006, Qwen3.5 397B A17B $0.0016 per turn.
List prices
At a glance
- Coding index
- Trinity Large Thinking not benchmarked, Qwen3.5 397B A17B not benchmarked.
- Widest category
- Coding, 19.2 points apart on average over 7 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): Trinity Large Thinking 38.0% against Qwen3.5 397B A17B 77.3%, 39.3 points apart on a 0 to 100 scale.
- Output price
- Trinity Large Thinking $0.80 against Qwen3.5 397B A17B $2.34 per million output tokens, 2.9x 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 | Qwen3.5 397B A17B | Ties |
|---|---|---|---|---|
| Coding | 0 | 7 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 7 | ||
| General | 0 | 19 | ||
| All shared boards | 0 | 46 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index07
| Benchmark | Trinity Large Thinking | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| LMArena WebDev | 1238 | 1400 | Qwen3.5 397B A17B |
| AA Coding Index | 25.8 | Not measured | Only Trinity Large Thinking measured |
| SciCode | 40.6% | 44.8% | Qwen3.5 397B A17B |
| Terminal-Bench Hard (Artificial Analysis run) | 22.7% | 40.9% | Qwen3.5 397B A17B |
| ALE-Bench | Not measured | 621.9 | Only Qwen3.5 397B A17B measured |
| LMArena Text: coding | 1357 | 1464 | Qwen3.5 397B A17B |
| LMArena Text: software and IT | 1362 | 1463 | Qwen3.5 397B A17B |
| LMArena WebDev: React | 1231 | 1388 | Qwen3.5 397B A17B |
| LMArena WebDev: HTML | 1240 | 1410 | Qwen3.5 397B A17B |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Trinity Large Thinking | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 21.4 | Qwen3.5 397B A17B |
| Epoch Capabilities Index | Not measured | 146.8 | Only Qwen3.5 397B A17B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Trinity Large Thinking | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | Not measured | Only Trinity Large Thinking measured |
| τ²-Bench Telecom | 90.1% | 95.6% | Qwen3.5 397B A17B |
| APEX-Agents | Not measured | 24.9% | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Trinity Large Thinking | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 75.2% | 89.3% | Qwen3.5 397B A17B |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | 29.0% | Qwen3.5 397B A17B |
| GPQA Diamond (Epoch AI run) | Not measured | 86.4% | Only Qwen3.5 397B A17B measured |
| Mystery game puzzles | Not measured | 18.0% | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts | 1342 | 1448 | Qwen3.5 397B A17B |
| LMArena Text: expert | 1359 | 1462 | Qwen3.5 397B A17B |
| LMArena Text: hard prompts in English | 1356 | 1450 | Qwen3.5 397B A17B |
| LMArena Vision: diagrams | Not measured | 1277 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: homework | Not measured | 1292 | Only Qwen3.5 397B A17B 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 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 88.9% | Only Qwen3.5 397B A17B measured |
| FrontierMath, tiers 1 to 3 | Not measured | 31.2% | Only Qwen3.5 397B A17B measured |
| LMArena Text: math | 1365 | 1453 | Qwen3.5 397B A17B |
| LMArena Text: mathematical work | 1350 | 1454 | Qwen3.5 397B A17B |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Trinity Large Thinking | Qwen3.5 397B A17B | 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 | 1457 | Qwen3.5 397B A17B |
| LMArena Text: medicine and healthcare | 1349 | 1455 | Qwen3.5 397B A17B |
| LMArena Text: legal and government | 1345 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: business and finance | 1329 | 1435 | Qwen3.5 397B A17B |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | Trinity Large Thinking | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| Design Arena: websites | 1137 | 1191 | Qwen3.5 397B A17B |
| Design Arena: UI components | 1045 | 1163 | Qwen3.5 397B A17B |
| Design Arena: game dev | 1079 | 1140 | Qwen3.5 397B A17B |
| Design Arena: data viz | 1098 | 1175 | Qwen3.5 397B A17B |
| Design Arena: 3D | 1082 | 1161 | Qwen3.5 397B A17B |
| Design Arena: all code categories | 1117 | 1180 | Qwen3.5 397B A17B |
| Design Arena: SVG | 1017 | 1140 | Qwen3.5 397B A17B |
| 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 index019
| Benchmark | Trinity Large Thinking | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| IFBench | 56.3% | 78.8% | Qwen3.5 397B A17B |
| Long context reasoning (AA-LCR) | 38.0% | 77.3% | Qwen3.5 397B A17B |
| DTBench | Not measured | 87.5% | Only Qwen3.5 397B A17B measured |
| LMCA | Not measured | 37.9% | Only Qwen3.5 397B A17B measured |
| Surface Evolver Bench | 15.6% | Not measured | Only Trinity Large Thinking measured |
| LMArena Text | 1340 | 1437 | Qwen3.5 397B A17B |
| LMArena Text: instruction following | 1326 | 1424 | Qwen3.5 397B A17B |
| LMArena Text: creative writing | 1308 | 1402 | Qwen3.5 397B A17B |
| LMArena Vision | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Text: English | 1356 | 1443 | Qwen3.5 397B A17B |
| LMArena Text: non-English | 1325 | 1430 | Qwen3.5 397B A17B |
| LMArena Text: Chinese | 1371 | 1498 | Qwen3.5 397B A17B |
| LMArena Text: German | 1356 | 1445 | Qwen3.5 397B A17B |
| LMArena Text: Japanese | 1312 | 1429 | Qwen3.5 397B A17B |
| LMArena Text: Korean | 1306 | 1384 | Qwen3.5 397B A17B |
| LMArena Text: French | 1366 | 1462 | Qwen3.5 397B A17B |
| LMArena Text: Spanish | 1327 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: Russian | 1338 | 1430 | Qwen3.5 397B A17B |
| LMArena Text: Polish | 1312 | 1447 | Qwen3.5 397B A17B |
| LMArena Text: multi-turn | 1320 | 1446 | Qwen3.5 397B A17B |
| LMArena Text: longer queries | 1318 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: writing and language | 1317 | 1415 | Qwen3.5 397B A17B |
| LMArena Text: entertainment and media | 1296 | 1399 | Qwen3.5 397B A17B |
| LMArena Vision: English | Not measured | 1268 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: Chinese | Not measured | 1314 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: reading text | Not measured | 1271 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: humor | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: captioning | Not measured | 1230 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: recognizing things | Not measured | 1265 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: creative writing | Not measured | 1260 | Only Qwen3.5 397B A17B 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 | Qwen3.5 397B A17B | 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 costs less
Repository review
50K input + 3K output tokens
Trinity Large Thinking costs less
Agent loop
200K input + 10K output tokens
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 | Qwen3.5 397B A17B |
|---|---|---|
| Maker | Arcee AI | Qwen |
| Weights | Open weights | Open weights |
| Released | April 1, 2026 | February 16, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.25 | $0.39 |
| Output $/Mtok | $0.80 | $2.34 |
| Coding index | Not benchmarked | Not benchmarked |
| 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 Qwen3.5 397B A17B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Trinity Large Thinking for output tokens 2.9x cheaper ($0.80 vs $2.34 per million) and work measured by LMArena WebDev or SciCode, where it leads.
Which is cheaper, Trinity Large Thinking or Qwen3.5 397B A17B?
Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for neither of them.
Which has the bigger context window, Trinity Large Thinking or Qwen3.5 397B A17B?
Neither: both take 262K tokens.
How many benchmarks is the Trinity Large Thinking vs Qwen3.5 397B A17B comparison based on?
46 benchmarks have a result for both models as of October 21, 2026. Trinity Large Thinking's coding index rests on 1 independent benchmark and Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.