Trinity Large Thinking vs Ministral 3 14B 2512
Trinity Large Thinking leads Ministral 3 14B 2512 on the Artificial Analysis Intelligence Index, 10.8 to 6.0, and Ministral 3 14B 2512 costs 4.0x less per output token ($0.20 vs $0.80 per million). Updated October 22, 2026; 7 benchmarks have a result for both.
Trinity Large Thinking or Ministral 3 14B 2512: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Trinity Large Thinking for work measured by AA Agentic Index, where it leads.
- Shared results
- 7
- Trinity Large Thinking only
- 45
- Ministral 3 14B 2512 only
- 0
- Like-for-like categories
- 4 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 6.0.
Same board, both measured
Agentic work
AA Agentic Index
Ministral 3 14B 2512
Ministral 3 14B 2512 leads, 1.1 against 1.0.
Same board, both measured
Web design
Design Arena: websites
Trinity Large Thinking
Trinity Large Thinking leads, 1137 against 1081.
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
Ministral 3 14B 2512
Trinity Large Thinking $0.0006, Ministral 3 14B 2512 $0.0003 per turn.
List prices
At a glance
- Coding index
- Trinity Large Thinking not benchmarked, Ministral 3 14B 2512 not benchmarked.
- Widest category
- Coding, 11.4 points apart on average over 1 shared benchmark.
- Widest single gap
- Design Arena: 3D: Trinity Large Thinking 1081 against Ministral 3 14B 2512 989, 11.5 points apart on a 0 to 100 scale.
- Output price
- Trinity Large Thinking $0.80 against Ministral 3 14B 2512 $0.20 per million output tokens, 4.0x 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 | Ministral 3 14B 2512 | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 0 | 1 | ||
| Web design | 4 | 0 | ||
| All shared boards | 6 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | Trinity Large Thinking | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| LMArena WebDev | 1238 | Not measured | Only Trinity Large Thinking measured |
| AA Coding Index | 25.8 | 14.4 | Trinity Large Thinking |
| SciCode | 40.6% | Not measured | Only Trinity Large Thinking measured |
| Terminal-Bench Hard (Artificial Analysis run) | 22.7% | Not measured | Only Trinity Large Thinking 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 | 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 31 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Trinity Large Thinking | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 6.0 | Trinity Large Thinking |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Trinity Large Thinking | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | 1.1 | Ministral 3 14B 2512 |
| τ²-Bench Telecom | 90.1% | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Trinity Large Thinking | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 75.2% | Not measured | Only Trinity Large Thinking measured |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | Not measured | Only Trinity Large Thinking 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 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Trinity Large Thinking | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| 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 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Trinity Large Thinking | Ministral 3 14B 2512 | 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 | 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 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Trinity Large Thinking | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| Design Arena: websites | 1137 | 1081 | Trinity Large Thinking |
| Design Arena: UI components | 1042 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: game dev | 1078 | 1037 | Trinity Large Thinking |
| Design Arena: data viz | 1098 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: 3D | 1081 | 989 | Trinity Large Thinking |
| Design Arena: all code categories | 1117 | 1064 | Trinity Large Thinking |
| 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 | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
| Benchmark | Trinity Large Thinking | Ministral 3 14B 2512 | Leader |
|---|---|---|---|
| IFBench | 56.3% | Not measured | Only Trinity Large Thinking measured |
| Long context reasoning (AA-LCR) | 38.0% | Not measured | Only Trinity Large Thinking measured |
| 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 26 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Trinity Large Thinking | Ministral 3 14B 2512 | 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
Ministral 3 14B 2512 costs less
Repository review
50K input + 3K output tokens
Ministral 3 14B 2512 costs less
Agent loop
200K input + 10K output tokens
Ministral 3 14B 2512 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 | Mistral Ministral 3 14B 2512 |
|---|---|---|
| Maker | Arcee AI | Mistral AI |
| Weights | Open weights | Open weights |
| Released | April 1, 2026 | December 2, 2025 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.25 | $0.20 |
| Output $/Mtok | $0.80 | $0.20 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Trinity Large Thinking better than Ministral 3 14B 2512 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Trinity Large Thinking for work measured by AA Agentic Index, where it leads.
Which is cheaper, Trinity Large Thinking or Ministral 3 14B 2512?
Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; Ministral 3 14B 2512 costs $0.20 and $0.20. Cost per solved task is known for neither of them.
Which has the bigger context window, Trinity Large Thinking or Ministral 3 14B 2512?
Neither: both take 262K tokens.
How many benchmarks is the Trinity Large Thinking vs Ministral 3 14B 2512 comparison based on?
7 benchmarks have a result for both models as of October 22, 2026. Trinity Large Thinking's coding index rests on 1 independent benchmark and Ministral 3 14B 2512's on 0. Where only one model has a result, the page says so instead of naming a winner.