Model comparison
Claude Opus 5 vs Trinity Large Thinking
Claude Opus 5 is the stronger model overall, scoring 67.8 to 38.6 on the Noometry Index. Trinity Large Thinking costs 26× less per token, which makes it the better buy when Claude Opus 5's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
Arcee AISummary
- They share 21 benchmarks with published results for both. Claude Opus 5 scores higher in 8 categories and Trinity Large Thinking in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 5 leads 77.2 to 16.9.
- The biggest single-benchmark swing is NYT Connections (extended): 94.3% for Claude Opus 5 and 16.5% for Trinity Large Thinking.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $5 / $25 for Claude Opus 5.
- Claude Opus 5 accepts more context: 1M tokens versus 262K.
- Trinity Large Thinking has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 5 | Trinity Large Thinking | |
|---|---|---|
| Provider | Anthropic | Arcee AI |
| Noometry Index | 67.8 | 38.6 |
| Released | 2026-07-24 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 1M | 262K |
| Max output | 128K | 80K |
| Input $ / M tokens | $5 | $0.25 |
| Output $ / M tokens | $25 | $0.80 |
| Results tracked | 57 | 24 |
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Category by category
Coding Claude Opus 5 leads
Claude Opus 5: 67.5 (#5), Trinity Large Thinking: 34.1 (#244)
| Benchmark | Claude Opus 5 | Trinity Large Thinking |
|---|---|---|
| LMArena WebDev | 1691 | 1238 |
| SciCode | 56.4% | 36.1% |
| LMArena Coding | 1534 | 1381 |
| DeepSWE | 73.6% | — |
| FrontierCode | 53.4% | — |
| CursorBench | 46.6% | — |
| FrontierSWE | 52% | — |
| WeirdML | 91.8% | — |
| ALE-Bench | 2,165 | — |
Agentic & Tool Use Not comparable
Claude Opus 5: 55.6 (#1), Trinity Large Thinking: —
| Benchmark | Claude Opus 5 | Trinity Large Thinking |
|---|---|---|
| APEX-Agents | 65.8% | — |
| OSWorld 2.0 | 31.4% | — |
| τ²-bench Banking | 48.7% | — |
| PostTrainBench | 35% | — |
| BALROG | 63.4% | — |
| GBAEval | 79.6% | — |
| GDP.pdf | 24% | — |
| Vending-Bench 2 | 11,182 | — |
Reasoning Claude Opus 5 leads
Claude Opus 5: 77.2 (#4), Trinity Large Thinking: 16.9 (#298)
| Benchmark | Claude Opus 5 | Trinity Large Thinking |
|---|---|---|
| NYT Connections (extended) | 94.3% | 16.5% |
| CritPt | 29.1% | 0.9% |
| LMArena Hard Prompts | 1526 | 1350 |
| ARC-AGI-2 | 90.4% | — |
| SimpleBench | 80.6% | — |
| ARC-AGI-1 | 97.5% | — |
| Chess Puzzles | 42% | — |
| Thematic Generalization | — | 41.6% |
| EBR-Bench | 45.7% | — |
| Mystery Game Puzzles | 59% | — |
| DTBench | 97.9% | — |
| LMCA | 64.5% | — |
| Surface Evolver Bench | — | 15.6% |
| Bench to the Future 3 | 0.12 | — |
| Epoch Capabilities Index | 162.78 | — |
Math Claude Opus 5 leads
Claude Opus 5: 86.2 (#8), Trinity Large Thinking: 37.6 (#149)
| Benchmark | Claude Opus 5 | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1531 | 1366 |
| FrontierMath (Tiers 1-3) | 85.6% | — |
| FrontierMath Tier 4 | 73.2% | — |
| OTIS Mock AIME 2024-2025 | 98.9% | — |
| ProofBench | 99% | — |
Knowledge Claude Opus 5 leads
Claude Opus 5: 66.8 (#9), Trinity Large Thinking: 40.9 (#113)
| Benchmark | Claude Opus 5 | Trinity Large Thinking |
|---|---|---|
| LMArena Expert | 1557 | 1360 |
| GPQA Diamond | 93.9% | — |
| SimpleQA Verified | 59.9% | — |
| Vectara Hallucination Rate | — | 6.9% |
Multimodal Not comparable
Claude Opus 5: 50.8 (#8), Trinity Large Thinking: —
| Benchmark | Claude Opus 5 | Trinity Large Thinking |
|---|---|---|
| LMArena Vision | 1319 | — |
| Blueprint-Bench 2 | 30.4% | — |
| Furniture Assembly | 60.8% | — |
| LMArena Document | 1516 | — |
Multilingual Claude Opus 5 leads
Claude Opus 5: 58.8 (#4), Trinity Large Thinking: 46.2 (#160)
| Benchmark | Claude Opus 5 | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1501 | 1325 |
| LMArena Chinese | 1574 | 1373 |
| LMArena French | 1519 | 1374 |
| LMArena German | 1524 | 1356 |
| LMArena Japanese | 1516 | 1311 |
| LMArena Korean | 1521 | 1306 |
| LMArena Russian | 1507 | 1337 |
| LMArena Spanish | 1519 | 1357 |
Instruction Following Claude Opus 5 leads
Claude Opus 5: 79.2 (#7), Trinity Large Thinking: 70.5 (#162)
| Benchmark | Claude Opus 5 | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1517 | 1334 |
Long Context Claude Opus 5 leads
Claude Opus 5: 46.5 (#21), Trinity Large Thinking: 41.3 (#144)
| Benchmark | Claude Opus 5 | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1515 | 1355 |
Writing & Preference Claude Opus 5 leads
Claude Opus 5: 79.2 (#1), Trinity Large Thinking: 53.8 (#158)
| Benchmark | Claude Opus 5 | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1507 | 1340 |
| LMArena Creative Writing | 1491 | 1320 |
| LMArena Multi-Turn | 1499 | 1342 |
| EQ-Bench Creative Writing | 2133 | — |
| EQ-Bench 4 | 1385 | — |
Frequently asked questions
Is Claude Opus 5 better than Trinity Large Thinking?
Claude Opus 5 is the stronger model overall, scoring 67.8 to 38.6 on the Noometry Index. Trinity Large Thinking costs 26× less per token, which makes it the better buy when Claude Opus 5's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 5 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 5 lists at $5 and $25.
Is Claude Opus 5 or Trinity Large Thinking better for coding?
Claude Opus 5 scores higher on coding benchmarks: 67.5 versus 34.1 in the Noometry coding category.
Which has the bigger context window?
Claude Opus 5 does, with 1M tokens against 262K.
How many benchmarks do Claude Opus 5 and Trinity Large Thinking share?
21 benchmarks have published results for both models. Claude Opus 5 has 57 scored results on Noometry and Trinity Large Thinking has 24.