Model comparison
Mistral Small 3.1 vs Trinity Large Thinking
Trinity Large Thinking is the stronger model overall, scoring 38.6 to 31.7 on the Noometry Index.
Last verified . 17 shared benchmarks.
Mistral AI
Arcee AISummary
- They share 17 benchmarks with published results for both. Mistral Small 3.1 scores higher in 2 categories and Trinity Large Thinking in 6 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Trinity Large Thinking leads 37.6 to 14.7.
- Both cost about the same: $0.35 input and $0.56 output per million tokens.
- Trinity Large Thinking accepts more context: 262K tokens versus 128K.
Side by side
| Mistral Small 3.1 | Trinity Large Thinking | |
|---|---|---|
| Provider | Mistral AI | Arcee AI |
| Noometry Index | 31.7 | 38.6 |
| Released | 2025-03-17 | 2026-04-01 |
| Weights | Open | Open |
| Context window | 128K | 262K |
| Max output | 102K | 80K |
| Input $ / M tokens | $0.35 | $0.25 |
| Output $ / M tokens | $0.56 | $0.80 |
| Results tracked | 28 | 24 |
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Category by category
Coding Mistral Small 3.1 leads
Mistral Small 3.1: 38.3 (#179), Trinity Large Thinking: 34.1 (#244)
| Benchmark | Mistral Small 3.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Coding | 1309 | 1381 |
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |
Reasoning Mistral Small 3.1 leads
Mistral Small 3.1: 19.7 (#254), Trinity Large Thinking: 16.9 (#298)
| Benchmark | Mistral Small 3.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Hard Prompts | 1278 | 1350 |
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Chess Puzzles | 1% | — |
| Thematic Generalization | — | 41.6% |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 127.48 | — |
Math Trinity Large Thinking leads
Mistral Small 3.1: 14.7 (#301), Trinity Large Thinking: 37.6 (#149)
| Benchmark | Mistral Small 3.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1262 | 1366 |
| OTIS Mock AIME 2024-2025 | 3.9% | — |
| Omni-MATH | 24.8% | — |
Knowledge Trinity Large Thinking leads
Mistral Small 3.1: 22.6 (#271), Trinity Large Thinking: 40.9 (#113)
| Benchmark | Mistral Small 3.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Expert | 1257 | 1360 |
| GPQA Diamond | 41.9% | — |
| MMLU-Pro | 61% | — |
| Vectara Hallucination Rate | — | 6.9% |
| GPQA (HELM) | 39.2% | — |
Multimodal Not comparable
Mistral Small 3.1: 33.2 (#99), Trinity Large Thinking: —
| Benchmark | Mistral Small 3.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Vision | 1136 | — |
Multilingual Trinity Large Thinking leads
Mistral Small 3.1: 41.2 (#209), Trinity Large Thinking: 46.2 (#160)
| Benchmark | Mistral Small 3.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1255 | 1325 |
| LMArena Chinese | 1253 | 1373 |
| LMArena French | 1273 | 1374 |
| LMArena German | 1266 | 1356 |
| LMArena Japanese | 1208 | 1311 |
| LMArena Korean | 1206 | 1306 |
| LMArena Russian | 1263 | 1337 |
| LMArena Spanish | 1283 | 1357 |
Instruction Following Trinity Large Thinking leads
Mistral Small 3.1: 63.6 (#230), Trinity Large Thinking: 70.5 (#162)
| Benchmark | Mistral Small 3.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1264 | 1334 |
| IFEval | 75% | — |
Long Context Trinity Large Thinking leads
Mistral Small 3.1: 39.5 (#178), Trinity Large Thinking: 41.3 (#144)
| Benchmark | Mistral Small 3.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1299 | 1355 |
Writing & Preference Trinity Large Thinking leads
Mistral Small 3.1: 37.0 (#259), Trinity Large Thinking: 53.8 (#158)
| Benchmark | Mistral Small 3.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1277 | 1340 |
| LMArena Creative Writing | 1253 | 1320 |
| LMArena Multi-Turn | 1270 | 1342 |
| EQ-Bench Creative Writing | 761 | — |
| WildBench | 78.8% | — |
Frequently asked questions
Is Mistral Small 3.1 better than Trinity Large Thinking?
Trinity Large Thinking is the stronger model overall, scoring 38.6 to 31.7 on the Noometry Index.
Which is cheaper, Mistral Small 3.1 or Trinity Large Thinking?
Trinity Large Thinking is cheaper. It lists at $0.25 per million input tokens and $0.80 per million output tokens; Mistral Small 3.1 lists at $0.35 and $0.56.
Is Mistral Small 3.1 or Trinity Large Thinking better for coding?
Mistral Small 3.1 scores higher on coding benchmarks: 38.3 versus 34.1 in the Noometry coding category.
Which has the bigger context window?
Trinity Large Thinking does, with 262K tokens against 128K.
How many benchmarks do Mistral Small 3.1 and Trinity Large Thinking share?
17 benchmarks have published results for both models. Mistral Small 3.1 has 28 scored results on Noometry and Trinity Large Thinking has 24.