Analysis Summary
Trinity Large Thinking is Arcee AI's reasoning-focused model, offering a 262K token context window with tool use and function calling. The intelligence index of 24.5 places it in the limited-to-moderate tier, and the agentic index of 56.4 suggests reasonable but not leading multi-step task performance.
For businesses, it suits mid-complexity workflows where cost control matters more than frontier reasoning quality. The long context is useful for document review or extended conversations, and the thinking orientation may help with structured analysis tasks. The absence of vision limits its applicability to text-only pipelines, and the lcr score of 0.33 indicates weaker long-context retrieval than competitors at this price point.
At $0.25 input and $0.80 output, pricing is competitive. Teams running moderate-volume text workflows who need a budget-conscious reasoning model with tool use should consider it, but expect to validate quality carefully against more established alternatives.
Assessed July 10, 2026
Editorial notes
Arcee AI Trinity Large Thinking offers a 262K context and tool use at competitive pricing, with a moderate intelligence index of 24.5 and decent agentic performance for mid-tier workloads.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
Arcee AI Trinity Large Thinking offers a 262K context and tool use at competitive pricing, with a moderate intelligence index of 24.5 and decent agentic performance for mid-tier workloads.
Benchmark scores
Magenta = intelligence Ā· Ink = technical/agentic Ā· Cyan = content & long-context Ā· Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
24.5 Intelligence IndexĀ·56.4 Agentic Index
How Arcee AI: Trinity Large Thinking compares
Arcee AI: Trinity Large Thinking ranks #121 of 395 AI models we track for overall intelligence, #61 of 302 for agentic tasks. Its 262K-token context window is larger than 79% of the models we list. At $0.22 per million input tokens it is cheaper than 50% of comparable models.
Dark bar = input Ā· light bar = output, scaled to the priciest peer.
1M tokens ā 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on value. The pulled-in intelligence corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side āPricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.22 | $0.000220 |
| Output | $0.85 | $0.000850 |
What would Arcee AI: Trinity Large Thinking cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 620 models ā Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Arcee AI: Trinity Large Thinking for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Arcee AI: Trinity Large Thinking
Trinity 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: https://youtu.be/Gc82AXLa0Rg?si=4RLn6WBz33qT--B7..
Explore Related Models
Frequently asked questions about Arcee AI: Trinity Large Thinking
How much does Arcee AI: Trinity Large Thinking cost?
Arcee AI: Trinity Large Thinking costs $0.22 per million input tokens and $0.85 per million output tokens.
What is the context window of Arcee AI: Trinity Large Thinking?
Arcee AI: Trinity Large Thinking has a context window of 262,144 tokens (262K).
What can Arcee AI: Trinity Large Thinking do?
Arcee AI: Trinity Large Thinking supports tool use and function calling.
Who created Arcee AI: Trinity Large Thinking?
Arcee AI: Trinity Large Thinking is developed by Arcee AI and was released on April 1, 2026.
Data sourced from the OpenRouter API, Artificial Analysis, the Hugging Face Open LLM Leaderboard and our own internal testing. Scores are editorially curated by our team.
Last updated: July 25, 2026 4:42 pm