Noometry

Model comparison

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.

Last verified . 23 shared benchmarks.

Claude Opus 4.7 Anthropic

58.3

Rank #19 Confirmed

Trinity Large Thinking Arcee AI

38.6

Rank #185 Confirmed

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.

Side by side

Claude Opus 4.7Trinity Large Thinking
ProviderAnthropicArcee AI
Noometry Index58.338.6
Released2026-04-142026-04-01
WeightsProprietaryOpen
Context window1M262K
Max output128K80K
Input $ / M tokens$5$0.25
Output $ / M tokens$25$0.80
Results tracked6624

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Category by category

Coding Claude Opus 4.7 leads

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

BenchmarkClaude Opus 4.7Trinity Large Thinking
LMArena WebDev15581238
SciCode54.5%36.1%
LMArena Coding15181381
SWE-bench Verified83.5%—
FrontierCode38.5%—
GSO44.1%—
WeirdML76.4%—
MirrorCode31.1%—
ALE-Bench1,323—

Agentic & Tool Use Not comparable

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

BenchmarkClaude Opus 4.7Trinity Large Thinking
Terminal-Bench80.2%—
APEX-Agents49.2%—
OSWorld 2.018.2%—
τ²-bench Banking40.2%—
PostTrainBench28.6%—
ExploitBench26.5%—
GBAEval43.8%—
GDP.pdf21%—
LMArena Search1233—
Vending-Bench 210,937—

Reasoning Claude Opus 4.7 leads

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

BenchmarkClaude Opus 4.7Trinity Large Thinking
NYT Connections (extended)39%16.5%
CritPt12%0.9%
Thematic Generalization72.8%41.6%
LMArena Hard Prompts15061350
ARC-AGI-275.8%—
SimpleBench61.7%—
Kagi LLM Benchmark80.7%—
ARC-AGI-193.5%—
Chess Puzzles30%—
EBR-Bench19%—
Mystery Game Puzzles28%—
DTBench94.7%—
LMCA52.2%—
Surface Evolver Bench—15.6%
Epoch Capabilities Index156.25—
ForecastBench60.3—

Math Claude Opus 4.7 leads

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

BenchmarkClaude Opus 4.7Trinity Large Thinking
LMArena Math14991366
FrontierMath (Tiers 1-3)70.2%—
FrontierMath Tier 431.7%—
MathArena Final-Answer Competitions73.6%—
OTIS Mock AIME 2024-202597.8%—
ProofBench54%—
FrontierMath (Feb 2025 set)43.8%—
FrontierMath Tier 4 (v1)22.9%—

Knowledge Claude Opus 4.7 leads

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

BenchmarkClaude Opus 4.7Trinity Large Thinking
Vectara Hallucination Rate12%6.9%
LMArena Expert15211360
GPQA Diamond90.2%—
Humanity's Last Exam36.2%—
SimpleQA Verified51.7%—

Multimodal Not comparable

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

BenchmarkClaude Opus 4.7Trinity Large Thinking
LMArena Vision1316—
Blueprint-Bench 224.5%—
Furniture Assembly33.3%—
LMArena Document1495—

Multilingual Claude Opus 4.7 leads

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

BenchmarkClaude Opus 4.7Trinity Large Thinking
LMArena Non-English14801325
LMArena Chinese15311373
LMArena French15031374
LMArena German14951356
LMArena Japanese14721311
LMArena Korean14641306
LMArena Russian14941337
LMArena Spanish14951357

Instruction Following Claude Opus 4.7 leads

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

BenchmarkClaude Opus 4.7Trinity Large Thinking
LMArena Instruction Following14981334

Long Context Claude Opus 4.7 leads

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

BenchmarkClaude Opus 4.7Trinity Large Thinking
LMArena Longer Query15051355

Writing & Preference Claude Opus 4.7 leads

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

BenchmarkClaude Opus 4.7Trinity Large Thinking
LMArena Text14901340
LMArena Creative Writing14861320
LMArena Multi-Turn15051342
EQ-Bench Creative Writing1914—
EQ-Bench 41311—

Frequently asked questions

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.

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