Arcee AI: Trinity Large Thinking

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...

Modalities

In / out price

$0.25 / $0.8 per 1M

Context

262K

Released

Apr 1, 2026

Why use Trinity Large Thinking

Step-by-step reasoning mode
Tool and function calling (agent-ready)

Pricing

Input	$0.25 / 1M tokens
Output	$0.8 / 1M tokens
Cached input (read)	$0.060 / 1M tokens

List prices via OpenRouter, checked daily. Real cost depends on the provider and on reasoning tokens.

How it ranks

Intelligence index10.8

Coding index25.8

Agentic index1

Source: Artificial Analysis (artificialanalysis.ai) via OpenRouter (openrouter.ai/rankings).

Cost calculator

Pick a task, set how often you run it, and compare what it costs on each model.

TaskInput tokens≈ 602 wordsOutput tokens≈ 1,504 wordsRuns per month

Input served from cache: 0%Repeated prompts (same instructions or document) are billed at the cheaper cache-read price where the model supports it.

Model	Per run	Per month	Per 1,000 runs
Arcee AI: Trinity Large Thinking	$0.0018	$1.80	$1.80

Estimates from list prices via OpenRouter; real bills vary by provider and reasoning tokens.

Will it fit? Context window simulator

Each square is about one page (500 words). Colored squares are your content; grey squares are free space in the model's context window.

Your content

Novel (90,000 words)

Total: about 120,000 tokens (≈ 90,226 words). Token counts are estimates.

Models

Zoom (square size): 6pxZoom out to see a whole million-token window at once.

Arcee AI: Trinity Large Thinking

262,144 tokens ≈ 395 pages

Fits: uses 46% of the window (room for 2× this much).

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