Trinity Large Thinking vs DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 leads Trinity Large Thinking on the Artificial Analysis Intelligence Index, 39.5 to 10.8, and DeepSeek V4.1 Flash 1017 costs 1.3x less per output token ($0.60 vs $0.80 per million). Updated October 22, 2026; 14 benchmarks have a result for both.
Trinity Large Thinking or DeepSeek V4.1 Flash 1017: which to pick
Only DeepSeek V4.1 Flash 1017 has a coding score, 70.3 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.
- Shared results
- 14
- Trinity Large Thinking only
- 38
- DeepSeek V4.1 Flash 1017 only
- 25
- Like-for-like categories
- 5 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 1017 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 leads, 39.5 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 1017
DeepSeek V4.1 Flash 1017 leads, 1311 against 1137.
Same board, both measured
General
Vals Index
No call
Only DeepSeek V4.1 Flash 1017 has a Vals Index result, 61.3%.
Directional only
Long documents
Listed context window
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4.1 Flash 1017
Trinity Large Thinking $0.0006, DeepSeek V4.1 Flash 1017 $0.0004 per turn.
List prices
At a glance
- Coding index
- Trinity Large Thinking not benchmarked, DeepSeek V4.1 Flash 1017 70.3 from 4 benchmarks.
- Widest category
- Coding, 49.4 points apart on average over 4 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: Trinity Large Thinking 1231 against DeepSeek V4.1 Flash 1017 1667, 61.6 points apart on a 0 to 100 scale.
- Output price
- Trinity Large Thinking $0.80 against DeepSeek V4.1 Flash 1017 $0.60 per million output tokens, 1.3x apart.
- Context window
- Trinity Large Thinking takes 262K tokens, DeepSeek V4.1 Flash 1017 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 1017 | Ties |
|---|---|---|---|---|
| Coding | 0 | 4 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| Web design | 0 | 7 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 14 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 96.0% | Only DeepSeek V4.1 Flash 1017 measured |
| LMArena WebDev | 1238 | 1664 | DeepSeek V4.1 Flash 1017 |
| AA Coding Index | 25.8 | Not measured | Only Trinity Large Thinking measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 31.8% | Only DeepSeek V4.1 Flash 1017 measured |
| Vibe Code Bench (Vals AI) | Not measured | 87.7% | Only DeepSeek V4.1 Flash 1017 measured |
| Code migration (Vals AI) | Not measured | 44.2% | Only DeepSeek V4.1 Flash 1017 measured |
| SciCode | 40.6% | 55.9% | DeepSeek V4.1 Flash 1017 |
| Terminal-Bench Hard (Artificial Analysis run) | 22.7% | Not measured | Only Trinity Large Thinking measured |
| ALE-Bench | Not measured | 1622.0 | Only DeepSeek V4.1 Flash 1017 measured |
| LMArena Text: coding | 1357 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: software and IT | 1362 | Not measured | Only Trinity Large Thinking measured |
| LMArena WebDev: React | 1231 | 1667 | DeepSeek V4.1 Flash 1017 |
| LMArena WebDev: HTML | 1240 | 1687 | DeepSeek V4.1 Flash 1017 |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 39.5 | DeepSeek V4.1 Flash 1017 |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: spreadsheets | Not measured | 1245 | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench research | Not measured | 79.5% | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench browser | Not measured | 76.0% | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench long agentic | Not measured | 50.9% | Only DeepSeek V4.1 Flash 1017 measured |
| Finance Agent (Vals AI) | Not measured | 57.0% | Only DeepSeek V4.1 Flash 1017 measured |
| Tax Agent Bench (Vals AI) | Not measured | 44.4% | Only DeepSeek V4.1 Flash 1017 measured |
| Legal Research Bench (Vals AI) | Not measured | 45.2% | Only DeepSeek V4.1 Flash 1017 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 14.2% | Only DeepSeek V4.1 Flash 1017 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 61.8% | Only DeepSeek V4.1 Flash 1017 measured |
| τ²-Bench Telecom | 90.1% | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 89.1% | Only DeepSeek V4.1 Flash 1017 measured |
| GPQA Diamond (Artificial Analysis run) | 75.2% | Not measured | Only Trinity Large Thinking measured |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | 43.3% | DeepSeek V4.1 Flash 1017 |
| GPQA Diamond (Epoch AI run) | Not measured | 93.2% | Only DeepSeek V4.1 Flash 1017 measured |
| Chess puzzles | Not measured | 46.0% | Only DeepSeek V4.1 Flash 1017 measured |
| Mystery game puzzles | Not measured | 49.0% | Only DeepSeek V4.1 Flash 1017 measured |
| LMArena Text: hard prompts | 1342 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: expert | 1359 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: hard prompts in English | 1356 | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 99.4% | Only DeepSeek V4.1 Flash 1017 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 71.2% | Only DeepSeek V4.1 Flash 1017 measured |
| FrontierMath, tier 4 | Not measured | 46.3% | Only DeepSeek V4.1 Flash 1017 measured |
| LMArena Text: math | 1365 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: mathematical work | 1350 | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash 1017 | 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 |
| SimpleQA Verified | Not measured | 42.5% | Only DeepSeek V4.1 Flash 1017 measured |
| LMArena Text: science | 1355 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: medicine and healthcare | 1349 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: legal and government | 1345 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: business and finance | 1329 | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| Design Arena: websites | 1137 | 1311 | DeepSeek V4.1 Flash 1017 |
| Design Arena: UI components | 1042 | 1303 | DeepSeek V4.1 Flash 1017 |
| Design Arena: game dev | 1078 | 1357 | DeepSeek V4.1 Flash 1017 |
| Design Arena: data viz | 1098 | 1330 | DeepSeek V4.1 Flash 1017 |
| Design Arena: 3D | 1081 | 1358 | DeepSeek V4.1 Flash 1017 |
| Design Arena: all code categories | 1117 | 1332 | DeepSeek V4.1 Flash 1017 |
| Design Arena: SVG | 1016 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: ASCII art | 1041 | 1242 | DeepSeek V4.1 Flash 1017 |
| LiveBench design | Not measured | 83.4% | Only DeepSeek V4.1 Flash 1017 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Trinity Large Thinking | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| Vals Index | Not measured | 61.3% | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench data analysis | Not measured | 79.5% | Only DeepSeek V4.1 Flash 1017 measured |
| IFBench | 56.3% | Not measured | Only Trinity Large Thinking measured |
| Long context reasoning (AA-LCR) | 38.0% | 82.7% | DeepSeek V4.1 Flash 1017 |
| Surface Evolver Bench | 15.6% | Not measured | Only Trinity Large Thinking measured |
| LMArena Text | 1340 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: instruction following | 1326 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: creative writing | 1308 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: English | 1356 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: non-English | 1325 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: Chinese | 1371 | Not measured | Only Trinity Large Thinking measured |
| 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 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: Spanish | 1327 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: Russian | 1338 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: Polish | 1312 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: multi-turn | 1320 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: longer queries | 1318 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: writing and language | 1317 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: entertainment and media | 1296 | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 24 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 1017 | 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
DeepSeek V4.1 Flash 1017 costs less
Repository review
50K input + 3K output tokens
DeepSeek V4.1 Flash 1017 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4.1 Flash 1017 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 1017 |
|---|---|---|
| Maker | Arcee AI | DeepSeek |
| Weights | Open weights | Open weights |
| Released | April 1, 2026 | October 17, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.25 | $0.15 |
| Output $/Mtok | $0.80 | $0.60 |
| Coding index | Not benchmarked | 70.3 |
| Independent measurements behind it | 1 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Trinity Large Thinking better than DeepSeek V4.1 Flash 1017 for coding?
Only DeepSeek V4.1 Flash 1017 has a coding score, 70.3 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 1017?
Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; DeepSeek V4.1 Flash 1017 costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, Trinity Large Thinking or DeepSeek V4.1 Flash 1017?
DeepSeek V4.1 Flash 1017, with 1.05M tokens against 262K.
How many benchmarks is the Trinity Large Thinking vs DeepSeek V4.1 Flash 1017 comparison based on?
14 benchmarks have a result for both models as of October 22, 2026. Trinity Large Thinking's coding index rests on 1 independent benchmark and DeepSeek V4.1 Flash 1017's on 4. Where only one model has a result, the page says so instead of naming a winner.