Model comparison
Laguna M.1 vs Trinity Large Thinking
Trinity Large Thinking is the stronger model overall, scoring 38.6 to 32.5 on the Noometry Index.
Last verified . 2 shared benchmarks.
Poolside
Arcee AISummary
- They share 2 benchmarks with published results for both. Laguna M.1 scores higher in 2 categories and Trinity Large Thinking in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where Trinity Large Thinking leads 37.6 to 21.1.
Side by side
| Laguna M.1 | Trinity Large Thinking | |
|---|---|---|
| Provider | Poolside | Arcee AI |
| Noometry Index | 32.5 | 38.6 |
| Released | 2026-04-28 | 2026-04-01 |
| Weights | Open | Open |
| Context window | 262K | 262K |
| Max output | 33K | 80K |
| Input $ / M tokens | — | $0.25 |
| Output $ / M tokens | — | $0.80 |
| Results tracked | 3 | 24 |
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Category by category
Coding Laguna M.1 leads
Laguna M.1: 36.6 (#204), Trinity Large Thinking: 34.1 (#244)
| Benchmark | Laguna M.1 | Trinity Large Thinking |
|---|---|---|
| LMArena WebDev | 1349 | 1238 |
| SciCode | — | 36.1% |
| LMArena Coding | — | 1381 |
Reasoning Laguna M.1 leads
Laguna M.1: 23.1 (#184), Trinity Large Thinking: 16.9 (#298)
| Benchmark | Laguna M.1 | Trinity Large Thinking |
|---|---|---|
| Surface Evolver Bench | 15.6% | 15.6% |
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Thematic Generalization | — | 41.6% |
| LMArena Hard Prompts | — | 1350 |
Math Trinity Large Thinking leads
Laguna M.1: 21.1 (#283), Trinity Large Thinking: 37.6 (#149)
| Benchmark | Laguna M.1 | Trinity Large Thinking |
|---|---|---|
| ProofBench | 0% | — |
| LMArena Math | — | 1366 |
Knowledge Not comparable
Laguna M.1: —, Trinity Large Thinking: 40.9 (#113)
| Benchmark | Laguna M.1 | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | — | 6.9% |
| LMArena Expert | — | 1360 |
Multilingual Not comparable
Laguna M.1: —, Trinity Large Thinking: 46.2 (#160)
| Benchmark | Laguna M.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | — | 1325 |
| LMArena Chinese | — | 1373 |
| LMArena French | — | 1374 |
| LMArena German | — | 1356 |
| LMArena Japanese | — | 1311 |
| LMArena Korean | — | 1306 |
| LMArena Russian | — | 1337 |
| LMArena Spanish | — | 1357 |
Instruction Following Not comparable
Laguna M.1: —, Trinity Large Thinking: 70.5 (#162)
| Benchmark | Laguna M.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | — | 1334 |
Long Context Not comparable
Laguna M.1: —, Trinity Large Thinking: 41.3 (#144)
| Benchmark | Laguna M.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | — | 1355 |
Writing & Preference Not comparable
Laguna M.1: —, Trinity Large Thinking: 53.8 (#158)
| Benchmark | Laguna M.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Text | — | 1340 |
| LMArena Creative Writing | — | 1320 |
| LMArena Multi-Turn | — | 1342 |
Frequently asked questions
Is Laguna M.1 better than Trinity Large Thinking?
Trinity Large Thinking is the stronger model overall, scoring 38.6 to 32.5 on the Noometry Index.
Is Laguna M.1 or Trinity Large Thinking better for coding?
Laguna M.1 scores higher on coding benchmarks: 36.6 versus 34.1 in the Noometry coding category.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do Laguna M.1 and Trinity Large Thinking share?
2 benchmarks have published results for both models. Laguna M.1 has 3 scored results on Noometry and Trinity Large Thinking has 24.