Model comparison
Claude Sonnet 4 vs Trinity Large Thinking
Claude Sonnet 4 is the stronger model overall, scoring 40.8 to 38.6 on the Noometry Index. Trinity Large Thinking costs 15× less per token, which makes it the better buy when Claude Sonnet 4's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
Arcee AISummary
- They share 20 benchmarks with published results for both. Claude Sonnet 4 scores higher in 7 categories and Trinity Large Thinking in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in coding, where Claude Sonnet 4 leads 43.5 to 34.1.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $3 / $15 for Claude Sonnet 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 Sonnet 4 | Trinity Large Thinking | |
|---|---|---|
| Provider | Anthropic | Arcee AI |
| Noometry Index | 40.8 | 38.6 |
| Released | 2025-05-22 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 200K | 262K |
| Max output | 64K | 80K |
| Input $ / M tokens | $3 | $0.25 |
| Output $ / M tokens | $15 | $0.80 |
| Results tracked | 58 | 24 |
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Category by category
Coding Claude Sonnet 4 leads
Claude Sonnet 4: 43.5 (#88), Trinity Large Thinking: 34.1 (#244)
| Benchmark | Claude Sonnet 4 | Trinity Large Thinking |
|---|---|---|
| SciCode | 40% | 36.1% |
| LMArena Coding | 1414 | 1381 |
| SWE-bench Verified (bash only) | 64.9% | — |
| Aider Polyglot | 61.3% | — |
| LMArena WebDev | — | 1238 |
| GSO | 4.9% | — |
| WeirdML | 46.1% | — |
| ALE-Bench | 655.35 | — |
Agentic & Tool Use Not comparable
Claude Sonnet 4: 38.5 (#31), Trinity Large Thinking: —
| Benchmark | Claude Sonnet 4 | Trinity Large Thinking |
|---|---|---|
| TheAgentCompany | 33.1% | — |
| Cybench | 35% | — |
| DeepResearch Bench | 46.6% | — |
| OSWorld | 43.9% | — |
| METR Time Horizons | 62% | — |
Reasoning Claude Sonnet 4 leads
Claude Sonnet 4: 22.9 (#187), Trinity Large Thinking: 16.9 (#298)
| Benchmark | Claude Sonnet 4 | Trinity Large Thinking |
|---|---|---|
| CritPt | 0.3% | 0.9% |
| LMArena Hard Prompts | 1372 | 1350 |
| ARC-AGI-2 | 5.9% | — |
| SimpleBench | 45.5% | — |
| Kagi LLM Benchmark | 73% | — |
| NYT Connections (extended) | — | 16.5% |
| ARC-AGI-1 | 40% | — |
| EnigmaEval | 3.1% | — |
| Thematic Generalization | — | 41.6% |
| DTBench | 77.1% | — |
| LMCA | 29% | — |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 141.69 | — |
| ForecastBench | 60.2 | — |
Math Claude Sonnet 4 leads
Claude Sonnet 4: 43.3 (#80), Trinity Large Thinking: 37.6 (#149)
| Benchmark | Claude Sonnet 4 | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1375 | 1366 |
| OTIS Mock AIME 2024-2025 | 71.1% | — |
| Omni-MATH | 60.2% | — |
| MATH Level 5 | 84.4% | — |
| FrontierMath (Feb 2025 set) | 4.1% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Too close to call
Claude Sonnet 4: 41.8 (#108), Trinity Large Thinking: 40.9 (#113)
| Benchmark | Claude Sonnet 4 | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | 10.3% | 6.9% |
| LMArena Expert | 1372 | 1360 |
| GPQA Diamond | 79.2% | — |
| Humanity's Last Exam | 7.8% | — |
| MMLU-Pro | 84.3% | — |
| Confabulations | 13.2% | — |
| GPQA (HELM) | 70.6% | — |
Multimodal Not comparable
Claude Sonnet 4: 26.2 (#121), Trinity Large Thinking: —
| Benchmark | Claude Sonnet 4 | Trinity Large Thinking |
|---|---|---|
| LMArena Vision | 1191 | — |
| GeoBench | 37% | — |
| VPCT | 34% | — |
| MindCube | 44.8% | — |
Multilingual Too close to call
Claude Sonnet 4: 46.7 (#156), Trinity Large Thinking: 46.2 (#160)
| Benchmark | Claude Sonnet 4 | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1333 | 1325 |
| LMArena Chinese | 1350 | 1373 |
| LMArena French | 1363 | 1374 |
| LMArena German | 1331 | 1356 |
| LMArena Japanese | 1302 | 1311 |
| LMArena Korean | 1291 | 1306 |
| LMArena Russian | 1355 | 1337 |
| LMArena Spanish | 1357 | 1357 |
Instruction Following Claude Sonnet 4 leads
Claude Sonnet 4: 71.7 (#145), Trinity Large Thinking: 70.5 (#162)
| Benchmark | Claude Sonnet 4 | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1376 | 1334 |
| IFEval | 84% | — |
Long Context Trinity Large Thinking leads
Claude Sonnet 4: 33.7 (#259), Trinity Large Thinking: 41.3 (#144)
| Benchmark | Claude Sonnet 4 | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1398 | 1355 |
| Fiction.LiveBench | 46.9% | — |
Writing & Preference Claude Sonnet 4 leads
Claude Sonnet 4: 57.1 (#132), Trinity Large Thinking: 53.8 (#158)
| Benchmark | Claude Sonnet 4 | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1351 | 1340 |
| LMArena Creative Writing | 1345 | 1320 |
| LMArena Multi-Turn | 1376 | 1342 |
| Short-Story Creative Writing | 81.4% | — |
| EQ-Bench Creative Writing | 1483 | — |
| WildBench | 83.8% | — |
Frequently asked questions
Is Claude Sonnet 4 better than Trinity Large Thinking?
Claude Sonnet 4 is the stronger model overall, scoring 40.8 to 38.6 on the Noometry Index. Trinity Large Thinking costs 15× less per token, which makes it the better buy when Claude Sonnet 4's lead doesn't matter for your workload.
Which is cheaper, Claude Sonnet 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 Sonnet 4 lists at $3 and $15.
Is Claude Sonnet 4 or Trinity Large Thinking better for coding?
Claude Sonnet 4 scores higher on coding benchmarks: 43.5 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 Sonnet 4 and Trinity Large Thinking share?
20 benchmarks have published results for both models. Claude Sonnet 4 has 58 scored results on Noometry and Trinity Large Thinking has 24.