Model comparison
Claude Opus 4 vs Trinity Large Thinking
Claude Opus 4 is the stronger model overall, scoring 43.1 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'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 scores higher in 7 categories and Trinity Large Thinking in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where Claude Opus 4 leads 47.2 to 34.1.
- The biggest single-benchmark swing is Vectara Hallucination Rate: 12% for Claude Opus 4 and 6.9% for Trinity Large Thinking.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $15 / $75 for Claude Opus 4.
- 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 | Trinity Large Thinking | |
|---|---|---|
| Provider | Anthropic | Arcee AI |
| Noometry Index | 43.1 | 38.6 |
| Released | 2025-05-22 | 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 | 56 | 24 |
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Category by category
Coding Claude Opus 4 leads
Claude Opus 4: 47.2 (#62), Trinity Large Thinking: 34.1 (#244)
| Benchmark | Claude Opus 4 | Trinity Large Thinking |
|---|---|---|
| LMArena Coding | 1442 | 1381 |
| SWE-bench Verified | 70.7% | — |
| SWE-bench Verified (bash only) | 67.6% | — |
| Aider Polyglot | 72% | — |
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |
| GSO | 6.9% | — |
| WeirdML | 43.7% | — |
| AlgoTune | 1.33 | — |
Agentic & Tool Use Not comparable
Claude Opus 4: 34.8 (#42), Trinity Large Thinking: —
| Benchmark | Claude Opus 4 | Trinity Large Thinking |
|---|---|---|
| Cybench | 38% | — |
| DeepResearch Bench | 46.8% | — |
| LMArena Search | 1127 | — |
| METR Time Horizons | 63.9% | — |
Reasoning Claude Opus 4 leads
Claude Opus 4: 27.3 (#121), Trinity Large Thinking: 16.9 (#298)
| Benchmark | Claude Opus 4 | Trinity Large Thinking |
|---|---|---|
| CritPt | 0.3% | 0.9% |
| LMArena Hard Prompts | 1399 | 1350 |
| ARC-AGI-2 | 8.6% | — |
| SimpleBench | 58.8% | — |
| Kagi LLM Benchmark | 74.3% | — |
| NYT Connections (extended) | — | 16.5% |
| ARC-AGI-1 | 35.7% | — |
| EnigmaEval | 5.6% | — |
| Thematic Generalization | — | 41.6% |
| DTBench | 81.6% | — |
| LMCA | 37.4% | — |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 142.67 | — |
| ForecastBench | 61.1 | — |
Math Claude Opus 4 leads
Claude Opus 4: 42.0 (#86), Trinity Large Thinking: 37.6 (#149)
| Benchmark | Claude Opus 4 | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1390 | 1366 |
| OTIS Mock AIME 2024-2025 | 64.4% | — |
| Omni-MATH | 61.6% | — |
| MATH Level 5 | 85% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Claude Opus 4 leads
Claude Opus 4: 44.0 (#88), Trinity Large Thinking: 40.9 (#113)
| Benchmark | Claude Opus 4 | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | 12% | 6.9% |
| LMArena Expert | 1386 | 1360 |
| GPQA Diamond | 76.3% | — |
| Humanity's Last Exam | 10.7% | — |
| MMLU-Pro | 87.5% | — |
| Confabulations | 15.9% | — |
| GPQA (HELM) | 70.8% | — |
Multimodal Not comparable
Claude Opus 4: 31.5 (#106), Trinity Large Thinking: —
| Benchmark | Claude Opus 4 | Trinity Large Thinking |
|---|---|---|
| LMArena Vision | 1192 | — |
| GeoBench | 49% | — |
| VPCT | 38% | — |
Multilingual Claude Opus 4 leads
Claude Opus 4: 48.8 (#138), Trinity Large Thinking: 46.2 (#160)
| Benchmark | Claude Opus 4 | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1362 | 1325 |
| LMArena Chinese | 1386 | 1373 |
| LMArena French | 1372 | 1374 |
| LMArena German | 1391 | 1356 |
| LMArena Japanese | 1331 | 1311 |
| LMArena Korean | 1321 | 1306 |
| LMArena Russian | 1392 | 1337 |
| LMArena Spanish | 1389 | 1357 |
Instruction Following Claude Opus 4 leads
Claude Opus 4: 77.1 (#28), Trinity Large Thinking: 70.5 (#162)
| Benchmark | Claude Opus 4 | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1406 | 1334 |
| IFEval | 91.8% | — |
Long Context Trinity Large Thinking leads
Claude Opus 4: 39.6 (#172), Trinity Large Thinking: 41.3 (#144)
| Benchmark | Claude Opus 4 | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1422 | 1355 |
| Fiction.LiveBench | 61.1% | — |
Writing & Preference Claude Opus 4 leads
Claude Opus 4: 61.2 (#89), Trinity Large Thinking: 53.8 (#158)
| Benchmark | Claude Opus 4 | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1377 | 1340 |
| LMArena Creative Writing | 1387 | 1320 |
| LMArena Multi-Turn | 1396 | 1342 |
| Short-Story Creative Writing | 83.6% | — |
| EQ-Bench Creative Writing | 1580 | — |
| WildBench | 85.2% | — |
Frequently asked questions
Is Claude Opus 4 better than Trinity Large Thinking?
Claude Opus 4 is the stronger model overall, scoring 43.1 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's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 4 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 lists at $15 and $75.
Is Claude Opus 4 or Trinity Large Thinking better for coding?
Claude Opus 4 scores higher on coding benchmarks: 47.2 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 and Trinity Large Thinking share?
19 benchmarks have published results for both models. Claude Opus 4 has 56 scored results on Noometry and Trinity Large Thinking has 24.