Trinity Large Thinking vs Mistral Small 4
Mistral Small 4 leads Trinity Large Thinking on the Artificial Analysis Intelligence Index, 11.3 to 10.8, and Mistral Small 4 costs 1.3x less per output token ($0.60 vs $0.80 per million). Updated October 22, 2026; 10 benchmarks have a result for both.
Trinity Large Thinking or Mistral Small 4: 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 Coding Index or AA Intelligence Index, where it leads.
- Shared results
- 10
- Trinity Large Thinking only
- 42
- Mistral Small 4 only
- 5
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Mistral Small 4
Mistral Small 4 leads, 11.3 against 10.8.
Same board, both measured
Agentic work
AA Agentic Index
Trinity Large Thinking
Trinity Large Thinking leads, 1.0 against 0.8.
Same board, both measured
Web design
Design Arena: websites
No call
Only Trinity Large Thinking has a Design Arena: websites result, 1137.
Directional only
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 4
Trinity Large Thinking $0.0006, Mistral Small 4 $0.0004 per turn.
List prices
At a glance
- Coding index
- Trinity Large Thinking not benchmarked, Mistral Small 4 not benchmarked.
- Widest category
- Agentic work, 24.5 points apart on average over 2 shared benchmarks.
- Widest single gap
- τ²-Bench Telecom: Trinity Large Thinking 90.1% against Mistral Small 4 41.2%, 48.8 points apart on a 0 to 100 scale.
- Output price
- Trinity Large Thinking $0.80 against Mistral Small 4 $0.60 per million output tokens, 1.3x 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 | Mistral Small 4 | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 1 | 1 | ||
| General | 1 | 1 | ||
| All shared boards | 6 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
| Benchmark | Trinity Large Thinking | Mistral Small 4 | Leader |
|---|---|---|---|
| LMArena WebDev | 1238 | Not measured | Only Trinity Large Thinking measured |
| AA Coding Index | 25.8 | 26.6 | Mistral Small 4 |
| Vibe Code Bench (Vals AI) | Not measured | 0.0% | Only Mistral Small 4 measured |
| SciCode | 40.6% | 38.8% | Trinity Large Thinking |
| Terminal-Bench Hard (Artificial Analysis run) | 22.7% | 17.4% | Trinity Large Thinking |
| ALE-Bench | Not measured | 497.6 | Only Mistral Small 4 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 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Trinity Large Thinking | Mistral Small 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 11.3 | Mistral Small 4 |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Trinity Large Thinking | Mistral Small 4 | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | 0.8 | Trinity Large Thinking |
| τ²-Bench Telecom | 90.1% | 41.2% | Trinity Large Thinking |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Trinity Large Thinking | Mistral Small 4 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 75.2% | 76.9% | Mistral Small 4 |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | 9.9% | Trinity Large Thinking |
| 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 |
| Kagi LLM Benchmark | Not measured | 40.5% | Only Mistral Small 4 measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Trinity Large Thinking | Mistral Small 4 | 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 | Mistral Small 4 | 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 designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Trinity Large Thinking | Mistral Small 4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1137 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: UI components | 1042 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: game dev | 1078 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: data viz | 1098 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: 3D | 1081 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: all code categories | 1117 | Not measured | Only Trinity Large Thinking measured |
| 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 | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Trinity Large Thinking | Mistral Small 4 | Leader |
|---|---|---|---|
| IFBench | 56.3% | 48.2% | Trinity Large Thinking |
| Long context reasoning (AA-LCR) | 38.0% | 49.7% | Mistral Small 4 |
| DTBench | Not measured | 70.9% | Only Mistral Small 4 measured |
| LMCA | Not measured | 20.6% | Only Mistral Small 4 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 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Trinity Large Thinking | Mistral Small 4 | 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
Mistral Small 4 costs less
Repository review
50K input + 3K output tokens
Mistral Small 4 costs less
Agent loop
200K input + 10K output tokens
Mistral Small 4 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 Small 4 |
|---|---|---|
| Maker | Arcee AI | Mistral AI |
| Weights | Open weights | Open weights |
| Released | April 1, 2026 | March 16, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.25 | $0.15 |
| Output $/Mtok | $0.80 | $0.60 |
| 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 Mistral Small 4 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 Coding Index or AA Intelligence Index, where it leads.
Which is cheaper, Trinity Large Thinking or Mistral Small 4?
Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; Mistral Small 4 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 Mistral Small 4?
Neither: both take 262K tokens.
How many benchmarks is the Trinity Large Thinking vs Mistral Small 4 comparison based on?
10 benchmarks have a result for both models as of October 22, 2026. Trinity Large Thinking's coding index rests on 1 independent benchmark and Mistral Small 4's on 1. Where only one model has a result, the page says so instead of naming a winner.