Side by side

See the difference.

Scores, capabilities and costs for the models you’re considering.

Scroll to compare models →

Comparison of Arcee AI: Trinity Large Thinking, Anthropic: Claude Sonnet 5.5
2 modelsarcee-aiArcee AI: Trinity Large ThinkingRemove ×anthropicAnthropic: Claude Sonnet 5.5Remove ×
What’s differentTrinity Large Thinking is a powerful open source reasoning model from the team at Arcee AI. It shows strong performance in PinchBench, agentic workloads, and reasoning tasks. Launch video:…Tuned for quick iteration on scoped fixes and documents; Anthropic favors Opus 5.5 for open-ended work needing sustained judgment.
DateApr 1, 2026ListedSep 28, 2026Released
Listed rate$0.25 in / $0.80 out/ 1M tokensArcee AI · via OpenRouter · all routes ↗arcee-ai$2.00 in / $10.00 out/ 1M tokensAmazon Bedrock · via OpenRouter · all routes ↗amazon-bedrock
Provider endpoints2 endpoints →11 endpoints →
AA Intelligence ↗4.3.2Not reported56 ↗Effort: max · Max, Default FallbackIndependent result
AA-Briefcase ↗1.1Not reported1,817.26 ↗Effort: max · Max, Default FallbackIndependent result
GDPval-AA ↗2.1Not reported1,837.82 ↗Effort: max · Max, Default FallbackIndependent result
AutomationBench-AA ↗AA Index 4.3.2 collectionNot reported71.77% ↗Effort: max · Max, Default FallbackIndependent result
Terminal-Bench 4.0 · AA ↗Not reported63.64% ↗Effort: max · Max, Default FallbackHarness unreportedIndependent result
SciCode ↗AA Index 4.3.2 collectionNot reported61% ↗AA · Under reviewEffort: max · Max, Default FallbackIndependent result
Humanity’s Last Exam ↗AA Index 4.3.2 collectionNot reported54.96% ↗Effort: max · Max, Default FallbackIndependent result
GDP.pdf ↗AA Index 4.3.2 collectionNot reported25.8% ↗Effort: max · Max, Default FallbackIndependent result
CritPt ↗AA Index 4.3.2 collectionNot reported31.43% ↗AA · Under reviewEffort: max · Max, Default FallbackIndependent result
AA-Omniscience ↗AA Index 4.3.2 collectionNot reported32.3 ↗Effort: max · Max, Default FallbackIndependent result
AA-LCR ↗1.1Not reported82.67% ↗Effort: max · Max, Default FallbackIndependent result
LiveBench ↗2.0 · 2026-10-14 (dataset 2026-09-02)Not reported82.46% ↗Effort: max · single run · equal mean of 7 suitesIndependent result
LiveBench Design ↗2.0 · 2026-10-14 (dataset 2026-09-02)Not reported85% ↗Effort: max · single runIndependent result
LiveBench Research ↗2.0 · 2026-10-14 (dataset 2026-09-02)Not reported83.6% ↗Effort: max · single runIndependent result
LiveBench Browser Use ↗2.0 · 2026-10-14 (dataset 2026-09-02)Not reported84% ↗Effort: max · single runIndependent result
LiveBench Coding ↗2.0 · 2026-10-14 (dataset 2026-09-02)Not reported94.7% ↗Effort: max · single runIndependent result
LiveBench Agentic ↗2.0 · 2026-10-14 (dataset 2026-09-02)Not reported78.8% ↗Effort: max · single runIndependent result
LiveBench Data Analysis ↗2.0 · 2026-10-14 (dataset 2026-09-02)Not reported59.5% ↗Effort: max · single runIndependent result
LiveBench Reasoning ↗2.0 · 2026-10-14 (dataset 2026-09-02)Not reported91.6% ↗Effort: max · single runIndependent result
Context window262.1K1M
Max output80K128K
Parameters——
Tool callingSupportedSupported
Structured outputNot reportedSupported
Image inputNot reportedSupported
ReasoningSupportedSupported
Prompt cachingSupportedSupported
Open weightsSupportedNot reported

Add another model

Search all models →