Model comparison
MiniMax-M2.7 vs Trinity Large Thinking
MiniMax-M2.7 and Trinity Large Thinking score almost the same on the Noometry Index (37.7 vs 38.6), so choose on price, context window or the category you care about most.
Last verified . 23 shared benchmarks.
MiniMax
Arcee AISummary
- They share 23 benchmarks with published results for both. MiniMax-M2.7 scores higher in 6 categories and Trinity Large Thinking in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Trinity Large Thinking leads 37.6 to 25.9.
- The biggest single-benchmark swing is SciCode: 47% for MiniMax-M2.7 and 36.1% for Trinity Large Thinking.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M2.7.
- Trinity Large Thinking accepts more context: 262K tokens versus 205K.
Side by side
| MiniMax-M2.7 | Trinity Large Thinking | |
|---|---|---|
| Provider | MiniMax | Arcee AI |
| Noometry Index | 37.7 | 38.6 |
| Released | 2026-03-18 | 2026-04-01 |
| Weights | Open | Open |
| Context window | 205K | 262K |
| Max output | 131K | 80K |
| Input $ / M tokens | $0.30 | $0.25 |
| Output $ / M tokens | $1.20 | $0.80 |
| Results tracked | 30 | 24 |
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Category by category
Coding MiniMax-M2.7 leads
MiniMax-M2.7: 41.8 (#120), Trinity Large Thinking: 34.1 (#244)
| Benchmark | MiniMax-M2.7 | Trinity Large Thinking |
|---|---|---|
| LMArena WebDev | 1398 | 1238 |
| SciCode | 47% | 36.1% |
| LMArena Coding | 1454 | 1381 |
| WeirdML | 37% | — |
| ALE-Bench | 599.25 | — |
Agentic & Tool Use Not comparable
MiniMax-M2.7: 25.1 (#111), Trinity Large Thinking: —
| Benchmark | MiniMax-M2.7 | Trinity Large Thinking |
|---|---|---|
| Terminal-Bench | 45.1% | — |
| ExploitBench | 13.3% | — |
| GBAEval | 0% | — |
Reasoning MiniMax-M2.7 leads
MiniMax-M2.7: 19.7 (#253), Trinity Large Thinking: 16.9 (#298)
| Benchmark | MiniMax-M2.7 | Trinity Large Thinking |
|---|---|---|
| NYT Connections (extended) | 24.7% | 16.5% |
| CritPt | 0.6% | 0.9% |
| Thematic Generalization | 39.3% | 41.6% |
| LMArena Hard Prompts | 1422 | 1350 |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 145.85 | — |
Math Trinity Large Thinking leads
MiniMax-M2.7: 25.9 (#263), Trinity Large Thinking: 37.6 (#149)
| Benchmark | MiniMax-M2.7 | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1420 | 1366 |
| ProofBench | 3% | — |
Knowledge Trinity Large Thinking leads
MiniMax-M2.7: 37.7 (#152), Trinity Large Thinking: 40.9 (#113)
| Benchmark | MiniMax-M2.7 | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | 12.9% | 6.9% |
| LMArena Expert | 1444 | 1360 |
Multilingual MiniMax-M2.7 leads
MiniMax-M2.7: 50.3 (#123), Trinity Large Thinking: 46.2 (#160)
| Benchmark | MiniMax-M2.7 | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1382 | 1325 |
| LMArena Chinese | 1441 | 1373 |
| LMArena French | 1421 | 1374 |
| LMArena German | 1398 | 1356 |
| LMArena Japanese | 1262 | 1311 |
| LMArena Korean | 1313 | 1306 |
| LMArena Russian | 1383 | 1337 |
| LMArena Spanish | 1403 | 1357 |
Instruction Following MiniMax-M2.7 leads
MiniMax-M2.7: 74.1 (#103), Trinity Large Thinking: 70.5 (#162)
| Benchmark | MiniMax-M2.7 | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1405 | 1334 |
Long Context MiniMax-M2.7 leads
MiniMax-M2.7: 43.3 (#99), Trinity Large Thinking: 41.3 (#144)
| Benchmark | MiniMax-M2.7 | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1419 | 1355 |
Writing & Preference MiniMax-M2.7 leads
MiniMax-M2.7: 58.9 (#112), Trinity Large Thinking: 53.8 (#158)
| Benchmark | MiniMax-M2.7 | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1405 | 1340 |
| LMArena Creative Writing | 1354 | 1320 |
| LMArena Multi-Turn | 1412 | 1342 |
Frequently asked questions
Is MiniMax-M2.7 better than Trinity Large Thinking?
MiniMax-M2.7 and Trinity Large Thinking score almost the same on the Noometry Index (37.7 vs 38.6), so choose on price, context window or the category you care about most.
Which is cheaper, MiniMax-M2.7 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; MiniMax-M2.7 lists at $0.30 and $1.20.
Is MiniMax-M2.7 or Trinity Large Thinking better for coding?
MiniMax-M2.7 scores higher on coding benchmarks: 41.8 versus 34.1 in the Noometry coding category.
Which has the bigger context window?
Trinity Large Thinking does, with 262K tokens against 205K.
How many benchmarks do MiniMax-M2.7 and Trinity Large Thinking share?
23 benchmarks have published results for both models. MiniMax-M2.7 has 30 scored results on Noometry and Trinity Large Thinking has 24.