Trinity Large Thinking vs DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads Trinity Large Thinking on the Artificial Analysis Intelligence Index, 24.7 to 10.8, at about the same output price ($0.78 vs $0.80 per million). Updated October 21, 2026; 44 benchmarks have a result for both.
vs boards won of 44 shared
Trinity Large Thinking or DeepSeek V4.1 Flash: which to pick
Only DeepSeek V4.1 Flash has a coding score, 62.5 on the Vibe Coding Index; Trinity Large Thinking has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
Model ATrinity Large ThinkingArcee AINot benchmarked1 independent benchmarkNo cost per solved taskModel BDeepSeek V4.1 FlashDeepSeek62.5/1005 independent benchmarksNo cost per solved task
- Shared results
- 44
- Trinity Large Thinking only
- 8
- DeepSeek V4.1 Flash only
- 57
- Like-for-like categories
- 7 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
Only DeepSeek V4.1 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 24.7 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
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 1309 against 1137.
Same board, both measured
Long documents
Listed context window
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4.1 Flash
Trinity Large Thinking $0.0006, DeepSeek V4.1 Flash $0.0006 per turn.
List prices
At a glance
- Coding index
- Trinity Large Thinking not benchmarked, DeepSeek V4.1 Flash 62.5 from 5 benchmarks.
- Widest category
- Coding, 39.0 points apart on average over 6 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: Trinity Large Thinking 1231 against DeepSeek V4.1 Flash 1628, 61.6 points apart on a 0 to 100 scale.
- Output price
- Trinity Large Thinking $0.80 against DeepSeek V4.1 Flash $0.78 per million output tokens, 1.0x apart.
- Context window
- Trinity Large Thinking takes 262K tokens, DeepSeek V4.1 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 | DeepSeek V4.1 Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 6 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 4 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 8 | ||
| General | 0 | 19 | ||
| All shared boards | 0 | 44 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 90.2% | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev | 1238 | 1618 | DeepSeek V4.1 Flash |
| AA Coding Index | 25.8 | Not measured | Only Trinity Large Thinking measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 19.7% | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench (Vals AI) | Not measured | 84.7% | Only DeepSeek V4.1 Flash measured |
| Code migration (Vals AI) | Not measured | 45.6% | Only DeepSeek V4.1 Flash measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only DeepSeek V4.1 Flash measured |
| IOI (Vals AI) | Not measured | 40.3% | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 74.5% | Only DeepSeek V4.1 Flash measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 46.5% | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 16.4% | Only DeepSeek V4.1 Flash measured |
| SkillsBench (Vals AI) | Not measured | 69.8% | Only DeepSeek V4.1 Flash measured |
| CyberBench (Vals AI) | Not measured | 73.7% | Only DeepSeek V4.1 Flash measured |
| SciCode | 40.6% | 51.9% | DeepSeek V4.1 Flash |
| Terminal-Bench Hard (Artificial Analysis run) | 22.7% | Not measured | Only Trinity Large Thinking measured |
| FrontierCode | Not measured | 43.9% | Only DeepSeek V4.1 Flash measured |
| ALE-Bench | Not measured | 1092.3 | Only DeepSeek V4.1 Flash measured |
| LMArena Text: coding | 1357 | 1502 | DeepSeek V4.1 Flash |
| LMArena Text: software and IT | 1362 | 1496 | DeepSeek V4.1 Flash |
| LMArena WebDev: React | 1231 | 1628 | DeepSeek V4.1 Flash |
| LMArena WebDev: HTML | 1240 | 1612 | DeepSeek V4.1 Flash |
| LMArena WebDev: from an image | Not measured | 1606 | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 24.7 | DeepSeek V4.1 Flash |
| Epoch Capabilities Index | Not measured | 155.9 | Only DeepSeek V4.1 Flash measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | Not measured | Only Trinity Large Thinking measured |
| LiveBench research | Not measured | 86.8% | Only DeepSeek V4.1 Flash measured |
| LiveBench browser | Not measured | 84.0% | Only DeepSeek V4.1 Flash measured |
| LiveBench long agentic | Not measured | 40.1% | Only DeepSeek V4.1 Flash measured |
| SREBench (Vals AI) | Not measured | 0.8% | Only DeepSeek V4.1 Flash measured |
| Finance Agent (Vals AI) | Not measured | 53.5% | Only DeepSeek V4.1 Flash measured |
| Tax Agent Bench (Vals AI) | Not measured | 26.6% | Only DeepSeek V4.1 Flash measured |
| Legal Research Bench (Vals AI) | Not measured | 41.4% | Only DeepSeek V4.1 Flash measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 57.2% | Only DeepSeek V4.1 Flash measured |
| BioMysteryBench (Vals AI) | Not measured | 67.8% | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 0.0% | Only DeepSeek V4.1 Flash measured |
| Vals Science Index | Not measured | 29.6% | Only DeepSeek V4.1 Flash measured |
| τ²-Bench Telecom | 90.1% | Not measured | Only Trinity Large Thinking measured |
| APEX-Agents | Not measured | 39.5% | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 27 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 86.7% | Only DeepSeek V4.1 Flash measured |
| MysteryMechanism (Vals AI) | Not measured | 21.2% | Only DeepSeek V4.1 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 75.2% | Not measured | Only Trinity Large Thinking measured |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | 39.2% | DeepSeek V4.1 Flash |
| GPQA Diamond (Epoch AI run) | Not measured | 89.8% | Only DeepSeek V4.1 Flash measured |
| ARC-AGI | Not measured | 94.5% | Only DeepSeek V4.1 Flash measured |
| ARC-AGI-2 | Not measured | 72.9% | Only DeepSeek V4.1 Flash measured |
| Chess puzzles | Not measured | 48.0% | Only DeepSeek V4.1 Flash measured |
| Mystery game puzzles | Not measured | 43.0% | Only DeepSeek V4.1 Flash measured |
| LMArena Text: hard prompts | 1342 | 1483 | DeepSeek V4.1 Flash |
| LMArena Text: expert | 1359 | 1501 | DeepSeek V4.1 Flash |
| LMArena Text: hard prompts in English | 1356 | 1488 | DeepSeek V4.1 Flash |
| LMArena Vision: diagrams | Not measured | 1297 | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: homework | Not measured | 1307 | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 98.3% | Only DeepSeek V4.1 Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 67.4% | Only DeepSeek V4.1 Flash measured |
| FrontierMath, tier 4 | Not measured | 26.8% | Only DeepSeek V4.1 Flash measured |
| ProofBench | Not measured | 54.0% | Only DeepSeek V4.1 Flash measured |
| LMArena Text: math | 1365 | 1478 | DeepSeek V4.1 Flash |
| LMArena Text: mathematical work | 1350 | 1485 | DeepSeek V4.1 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 | DeepSeek V4.1 Flash | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | Not measured | 83.3% | Only DeepSeek V4.1 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 |
| MedCode (Vals AI) | Not measured | 41.2% | Only DeepSeek V4.1 Flash measured |
| SimpleQA Verified | Not measured | 42.9% | Only DeepSeek V4.1 Flash measured |
| LMArena Text: science | 1355 | 1469 | DeepSeek V4.1 Flash |
| LMArena Text: medicine and healthcare | 1349 | 1484 | DeepSeek V4.1 Flash |
| LMArena Text: legal and government | 1345 | 1443 | DeepSeek V4.1 Flash |
| LMArena Text: business and finance | 1329 | 1461 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 9 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1137 | 1309 | DeepSeek V4.1 Flash |
| Design Arena: UI components | 1045 | 1315 | DeepSeek V4.1 Flash |
| Design Arena: game dev | 1079 | 1330 | DeepSeek V4.1 Flash |
| Design Arena: data viz | 1098 | 1290 | DeepSeek V4.1 Flash |
| Design Arena: 3D | 1082 | 1356 | DeepSeek V4.1 Flash |
| Design Arena: all code categories | 1117 | 1320 | DeepSeek V4.1 Flash |
| Design Arena: SVG | 1017 | 1244 | DeepSeek V4.1 Flash |
| Design Arena: ASCII art | 1041 | 1265 | DeepSeek V4.1 Flash |
| LiveBench design | Not measured | 79.2% | Only DeepSeek V4.1 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index019
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 79.3% | Only DeepSeek V4.1 Flash measured |
| Public Benefits Bench (Vals AI) | Not measured | 64.3% | Only DeepSeek V4.1 Flash measured |
| SAGE (Vals AI) | Not measured | 47.9% | Only DeepSeek V4.1 Flash measured |
| MedScribe (Vals AI) | Not measured | 85.5% | Only DeepSeek V4.1 Flash measured |
| IFBench | 56.3% | Not measured | Only Trinity Large Thinking measured |
| Long context reasoning (AA-LCR) | 38.0% | 84.0% | DeepSeek V4.1 Flash |
| DTBench | Not measured | 89.9% | Only DeepSeek V4.1 Flash measured |
| LMCA | Not measured | 47.0% | Only DeepSeek V4.1 Flash measured |
| Surface Evolver Bench | 15.6% | 46.3% | DeepSeek V4.1 Flash |
| Furniture assembly | Not measured | 34.2% | Only DeepSeek V4.1 Flash measured |
| LMArena Text | 1340 | 1464 | DeepSeek V4.1 Flash |
| LMArena Text: instruction following | 1326 | 1473 | DeepSeek V4.1 Flash |
| LMArena Text: creative writing | 1308 | 1437 | DeepSeek V4.1 Flash |
| LMArena Vision | Not measured | 1278 | Only DeepSeek V4.1 Flash measured |
| LMArena Text: English | 1356 | 1473 | DeepSeek V4.1 Flash |
| LMArena Text: non-English | 1325 | 1449 | DeepSeek V4.1 Flash |
| LMArena Text: Chinese | 1371 | 1501 | DeepSeek V4.1 Flash |
| LMArena Text: German | 1356 | 1470 | DeepSeek V4.1 Flash |
| LMArena Text: Japanese | 1312 | 1432 | DeepSeek V4.1 Flash |
| LMArena Text: Korean | 1306 | 1436 | DeepSeek V4.1 Flash |
| LMArena Text: French | 1366 | 1465 | DeepSeek V4.1 Flash |
| LMArena Text: Spanish | 1327 | 1459 | DeepSeek V4.1 Flash |
| LMArena Text: Russian | 1338 | 1467 | DeepSeek V4.1 Flash |
| LMArena Text: Polish | 1312 | 1457 | DeepSeek V4.1 Flash |
| LMArena Text: multi-turn | 1320 | 1461 | DeepSeek V4.1 Flash |
| LMArena Text: longer queries | 1318 | 1473 | DeepSeek V4.1 Flash |
| LMArena Text: writing and language | 1317 | 1450 | DeepSeek V4.1 Flash |
| LMArena Text: entertainment and media | 1296 | 1445 | DeepSeek V4.1 Flash |
| LMArena Vision: English | Not measured | 1288 | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: Chinese | Not measured | 1327 | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: reading text | Not measured | 1282 | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: humor | Not measured | 1260 | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: creative writing | Not measured | 1275 | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 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
DeepSeek V4.1 Flash$0.0006Fits in one request
DeepSeek V4.1 Flash costs less
Repository review
50K input + 3K output tokens
Trinity Large Thinking$0.015Fits in one request
DeepSeek V4.1 Flash$0.013Fits in one request
DeepSeek V4.1 Flash costs less
Agent loop
200K input + 10K output tokens
Trinity Large Thinking$0.058Fits in one request
DeepSeek V4.1 Flash$0.050Fits in one request
DeepSeek V4.1 Flash 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 | DeepSeek V4.1 Flash |
|---|---|---|
| Maker | Arcee AI | DeepSeek |
| Weights | Open weights | Open weights |
| Released | April 1, 2026 | September 10, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.25 | $0.21 |
| Output $/Mtok | $0.80 | $0.78 |
| Coding index | Not benchmarked | 62.5 |
| Independent measurements behind it | 1 | 5 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Trinity Large Thinking better than DeepSeek V4.1 Flash for coding?
Only DeepSeek V4.1 Flash has a coding score, 62.5 on the Vibe Coding Index; Trinity Large Thinking has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Trinity Large Thinking or DeepSeek V4.1 Flash?
Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; DeepSeek V4.1 Flash costs $0.21 and $0.78. Cost per solved task is known for neither of them.
Which has the bigger context window, Trinity Large Thinking or DeepSeek V4.1 Flash?
DeepSeek V4.1 Flash, with 1.05M tokens against 262K.
How many benchmarks is the Trinity Large Thinking vs DeepSeek V4.1 Flash 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 DeepSeek V4.1 Flash's on 5. Where only one model has a result, the page says so instead of naming a winner.