Model comparison
Claude Opus 4.1 vs Trinity Large Thinking
Claude Opus 4.1 is the stronger model overall, scoring 41.0 to 38.6 on the Noometry Index. Trinity Large Thinking costs 77× less per token, which makes it the better buy when Claude Opus 4.1's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
Arcee AISummary
- They share 19 benchmarks with published results for both. Claude Opus 4.1 scores higher in 7 categories and Trinity Large Thinking in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Trinity Large Thinking leads 37.6 to 22.3.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $15 / $75 for Claude Opus 4.1.
- Trinity Large Thinking accepts more context: 262K tokens versus 200K.
- Trinity Large Thinking has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 4.1 | Trinity Large Thinking | |
|---|---|---|
| Provider | Anthropic | Arcee AI |
| Noometry Index | 41.0 | 38.6 |
| Released | 2025-08-05 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 200K | 262K |
| Max output | 32K | 80K |
| Input $ / M tokens | $15 | $0.25 |
| Output $ / M tokens | $75 | $0.80 |
| Results tracked | 48 | 24 |
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Category by category
Coding Claude Opus 4.1 leads
Claude Opus 4.1: 44.4 (#73), Trinity Large Thinking: 34.1 (#244)
| Benchmark | Claude Opus 4.1 | Trinity Large Thinking |
|---|---|---|
| LMArena WebDev | 1390 | 1238 |
| LMArena Coding | 1479 | 1381 |
| SWE-bench Verified | 73.3% | — |
| SciCode | — | 36.1% |
| WeirdML | 45.9% | — |
| ALE-Bench | 674.77 | — |
| AlgoTune | 1.34 | — |
Agentic & Tool Use Not comparable
Claude Opus 4.1: 35.0 (#41), Trinity Large Thinking: —
| Benchmark | Claude Opus 4.1 | Trinity Large Thinking |
|---|---|---|
| Terminal-Bench | 38% | — |
| GDPval | 43.6% | — |
| Cybench | 42% | — |
| DeepResearch Bench | 48.3% | — |
| LMArena Search | 1148 | — |
| METR Time Horizons | 66.8% | — |
Reasoning Claude Opus 4.1 leads
Claude Opus 4.1: 32.2 (#76), Trinity Large Thinking: 16.9 (#298)
| Benchmark | Claude Opus 4.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Hard Prompts | 1443 | 1350 |
| SimpleBench | 60% | — |
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Chess Puzzles | 7% | — |
| EnigmaEval | 7.2% | — |
| Thematic Generalization | — | 41.6% |
| EBR-Bench | 7.9% | — |
| Mystery Game Puzzles | 21% | — |
| DTBench | 80% | — |
| LMCA | 37.1% | — |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 144.12 | — |
| ForecastBench | 62 | — |
Math Trinity Large Thinking leads
Claude Opus 4.1: 22.3 (#277), Trinity Large Thinking: 37.6 (#149)
| Benchmark | Claude Opus 4.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1431 | 1366 |
| FrontierMath (Tiers 1-3) | 12.6% | — |
| FrontierMath Tier 4 | 2.4% | — |
| OTIS Mock AIME 2024-2025 | 68.9% | — |
| FrontierMath (Feb 2025 set) | 7.2% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Claude Opus 4.1 leads
Claude Opus 4.1: 42.0 (#101), Trinity Large Thinking: 40.9 (#113)
| Benchmark | Claude Opus 4.1 | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | 11.8% | 6.9% |
| LMArena Expert | 1439 | 1360 |
| GPQA Diamond | 77.3% | — |
| Humanity's Last Exam | 11.5% | — |
| Confabulations | 17.1% | — |
Multimodal Not comparable
Claude Opus 4.1: 26.8 (#119), Trinity Large Thinking: —
| Benchmark | Claude Opus 4.1 | Trinity Large Thinking |
|---|---|---|
| VPCT | 35% | — |
Multilingual Claude Opus 4.1 leads
Claude Opus 4.1: 52.0 (#95), Trinity Large Thinking: 46.2 (#160)
| Benchmark | Claude Opus 4.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1405 | 1325 |
| LMArena Chinese | 1427 | 1373 |
| LMArena French | 1431 | 1374 |
| LMArena German | 1413 | 1356 |
| LMArena Japanese | 1378 | 1311 |
| LMArena Korean | 1380 | 1306 |
| LMArena Russian | 1422 | 1337 |
| LMArena Spanish | 1448 | 1357 |
Instruction Following Claude Opus 4.1 leads
Claude Opus 4.1: 75.6 (#58), Trinity Large Thinking: 70.5 (#162)
| Benchmark | Claude Opus 4.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1435 | 1334 |
Long Context Claude Opus 4.1 leads
Claude Opus 4.1: 44.5 (#63), Trinity Large Thinking: 41.3 (#144)
| Benchmark | Claude Opus 4.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1455 | 1355 |
Writing & Preference Claude Opus 4.1 leads
Claude Opus 4.1: 62.4 (#74), Trinity Large Thinking: 53.8 (#158)
| Benchmark | Claude Opus 4.1 | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1419 | 1340 |
| LMArena Creative Writing | 1412 | 1320 |
| LMArena Multi-Turn | 1444 | 1342 |
| Short-Story Creative Writing | 84.7% | — |
Frequently asked questions
Is Claude Opus 4.1 better than Trinity Large Thinking?
Claude Opus 4.1 is the stronger model overall, scoring 41.0 to 38.6 on the Noometry Index. Trinity Large Thinking costs 77× less per token, which makes it the better buy when Claude Opus 4.1's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 4.1 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; Claude Opus 4.1 lists at $15 and $75.
Is Claude Opus 4.1 or Trinity Large Thinking better for coding?
Claude Opus 4.1 scores higher on coding benchmarks: 44.4 versus 34.1 in the Noometry coding category.
Which has the bigger context window?
Trinity Large Thinking does, with 262K tokens against 200K.
How many benchmarks do Claude Opus 4.1 and Trinity Large Thinking share?
19 benchmarks have published results for both models. Claude Opus 4.1 has 48 scored results on Noometry and Trinity Large Thinking has 24.