# Claude Opus 4.7 vs Trinity Large Thinking

> Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 38.6 on the Noometry Index. Trinity Large Thinking costs 26× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-opus-4-7-vs-trinity-large-thinking
- Last updated: 2026-10-11
- Shared benchmarks: 23

## Summary

- They share 23 benchmarks with published results for both. Claude Opus 4.7 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 4.7 leads 53.8 to 16.9.
- The biggest single-benchmark swing is Thematic Generalization: 72.8% for Claude Opus 4.7 and 41.6% 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 4.7.
- Claude Opus 4.7 accepts more context: 1M tokens versus 262K.
- Trinity Large Thinking has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 4.7 | Trinity Large Thinking |
|---|---|---|
| Provider | Anthropic | Arcee AI |
| Noometry Index | 58.3 | 38.6 |
| Rank | 19 | 185 |
| Context | 1M | 262K |
| Input $/M | $5 | $0.25 |
| Output $/M | $25 | $0.80 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 4.7: 59.6 (#13)
- Trinity Large Thinking: 34.1 (#244)

| Benchmark | Claude Opus 4.7 | Trinity Large Thinking |
|---|---|---|
| LMArena WebDev | 1558 | 1238 |
| SciCode | 54.5% | 36.1% |
| LMArena Coding | 1518 | 1381 |
| SWE-bench Verified | 83.5% | — |
| FrontierCode | 38.5% | — |
| GSO | 44.1% | — |
| WeirdML | 76.4% | — |
| MirrorCode | 31.1% | — |
| ALE-Bench | 1,323 | — |

## Agentic & Tool Use

- Claude Opus 4.7: 47.9 (#10)
- Trinity Large Thinking: —

| Benchmark | Claude Opus 4.7 | Trinity Large Thinking |
|---|---|---|
| Terminal-Bench | 80.2% | — |
| APEX-Agents | 49.2% | — |
| OSWorld 2.0 | 18.2% | — |
| τ²-bench Banking | 40.2% | — |
| PostTrainBench | 28.6% | — |
| ExploitBench | 26.5% | — |
| GBAEval | 43.8% | — |
| GDP.pdf | 21% | — |
| LMArena Search | 1233 | — |
| Vending-Bench 2 | 10,937 | — |

## Reasoning

- Claude Opus 4.7: 53.8 (#29)
- Trinity Large Thinking: 16.9 (#298)

| Benchmark | Claude Opus 4.7 | Trinity Large Thinking |
|---|---|---|
| NYT Connections (extended) | 39% | 16.5% |
| CritPt | 12% | 0.9% |
| Thematic Generalization | 72.8% | 41.6% |
| LMArena Hard Prompts | 1506 | 1350 |
| ARC-AGI-2 | 75.8% | — |
| SimpleBench | 61.7% | — |
| Kagi LLM Benchmark | 80.7% | — |
| ARC-AGI-1 | 93.5% | — |
| Chess Puzzles | 30% | — |
| EBR-Bench | 19% | — |
| Mystery Game Puzzles | 28% | — |
| DTBench | 94.7% | — |
| LMCA | 52.2% | — |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 156.25 | — |
| ForecastBench | 60.3 | — |

## Math

- Claude Opus 4.7: 66.7 (#26)
- Trinity Large Thinking: 37.6 (#149)

| Benchmark | Claude Opus 4.7 | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1499 | 1366 |
| FrontierMath (Tiers 1-3) | 70.2% | — |
| FrontierMath Tier 4 | 31.7% | — |
| MathArena Final-Answer Competitions | 73.6% | — |
| OTIS Mock AIME 2024-2025 | 97.8% | — |
| ProofBench | 54% | — |
| FrontierMath (Feb 2025 set) | 43.8% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |

## Knowledge

- Claude Opus 4.7: 62.6 (#23)
- Trinity Large Thinking: 40.9 (#113)

| Benchmark | Claude Opus 4.7 | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | 12% | 6.9% |
| LMArena Expert | 1521 | 1360 |
| GPQA Diamond | 90.2% | — |
| Humanity's Last Exam | 36.2% | — |
| SimpleQA Verified | 51.7% | — |

## Multimodal

- Claude Opus 4.7: 41.2 (#38)
- Trinity Large Thinking: —

| Benchmark | Claude Opus 4.7 | Trinity Large Thinking |
|---|---|---|
| LMArena Vision | 1316 | — |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |

## Multilingual

- Claude Opus 4.7: 57.3 (#10)
- Trinity Large Thinking: 46.2 (#160)

| Benchmark | Claude Opus 4.7 | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1480 | 1325 |
| LMArena Chinese | 1531 | 1373 |
| LMArena French | 1503 | 1374 |
| LMArena German | 1495 | 1356 |
| LMArena Japanese | 1472 | 1311 |
| LMArena Korean | 1464 | 1306 |
| LMArena Russian | 1494 | 1337 |
| LMArena Spanish | 1495 | 1357 |

## Instruction Following

- Claude Opus 4.7: 78.4 (#10)
- Trinity Large Thinking: 70.5 (#162)

| Benchmark | Claude Opus 4.7 | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1498 | 1334 |

## Long Context

- Claude Opus 4.7: 46.2 (#25)
- Trinity Large Thinking: 41.3 (#144)

| Benchmark | Claude Opus 4.7 | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1505 | 1355 |

## Writing & Preference

- Claude Opus 4.7: 75.1 (#8)
- Trinity Large Thinking: 53.8 (#158)

| Benchmark | Claude Opus 4.7 | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1490 | 1340 |
| LMArena Creative Writing | 1486 | 1320 |
| LMArena Multi-Turn | 1505 | 1342 |
| EQ-Bench Creative Writing | 1914 | — |
| EQ-Bench 4 | 1311 | — |

## FAQ

### Is Claude Opus 4.7 better than Trinity Large Thinking?

Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 38.6 on the Noometry Index. Trinity Large Thinking costs 26× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

### Which is cheaper, Claude Opus 4.7 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; Claude Opus 4.7 lists at $5 and $25.

### Is Claude Opus 4.7 or Trinity Large Thinking better for coding?

Claude Opus 4.7 scores higher on coding benchmarks: 59.6 versus 34.1 in the Noometry coding category.

### Which has the bigger context window?

Claude Opus 4.7 does, with 1M tokens against 262K.

### How many benchmarks do Claude Opus 4.7 and Trinity Large Thinking share?

23 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and Trinity Large Thinking has 24.