openai
Trinity Large Thinking vs GPT-5.6 Luna
73.6 overall · $0.450 / 1M
// arcee-ai
Trinity Large Thinking
arcee-ai/trinity-large-thinking
reasoningtool callingprompt caching
Trinity Large Thinking costs $0.250 per 1M input tokens and $0.800 per 1M output tokens with a 262K-token context window.
A reasoning, tool-calling model from arcee-ai, released Apr 1, 2026. LiveBench hasn't published a run for it, so this page carries measured price and specs only — no benchmark numbers.
- Input / 1M
- $0.250
- Output / 1M
- $0.800
- Context
- 262K
- LiveBench overall
- Not evaluated
Specs and pricing
| Input price USD per 1M prompt tokens | $0.250 |
|---|---|
| Output price USD per 1M completion tokens, reasoning included | $0.800 |
| Blended price 3:1 input:output — #114 cheapest of 343 listed models | $0.387 |
| Cached input read Blank means not priced separately — not free | $0.060 |
| Cache write | — |
| Context window | 262,144 tokens |
| Max output | 80,000 tokens |
| Input modalities | text |
| Tool calling | Yes |
| Extended reasoning | Yes |
| Knowledge cutoff | — |
| Listed | Apr 1, 2026 |
What Trinity Large Thinking costs to run
Monthly list cost across five workload shapes, using the published cached-input rate where there is one. A floor, not a quote — batch discounts and cache writes aren't included.
| Workload | Per month |
|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $110.32/mo |
| RAG assistant 8K in / 600 out × 100K requests | $172.00/mo |
| Coding agent 40K in / 4K out × 20K requests | $157.60/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $300.50/mo |
| Bulk classification 500 in / 20 out × 5M requests | $610.00/mo |
Compare Trinity Large Thinking with
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Trinity Large Thinking FAQ
How much does Trinity Large Thinking cost?
Trinity Large Thinking lists at $0.250 per 1M input tokens and $0.800 per 1M output tokens, with cached input reads at $0.060 per 1M. A RAG assistant handling 100K requests a month (8K tokens in, 600 out) comes to about $172.00 at list price.
What is the context window of Trinity Large Thinking?
Trinity Large Thinking accepts up to 262,144 tokens of context and can return up to 80,000 output tokens per response.
Does Trinity Large Thinking support tool calling?
Yes — Trinity Large Thinking supports tool (function) calling and exposes extended reasoning. It accepts text input.
How does Trinity Large Thinking score on benchmarks?
LiveBench has not published a run for Trinity Large Thinking yet. Until it does, compare it on price and specs, or run your own evaluation on your own tasks.
What is the API model ID for Trinity Large Thinking?
On OpenRouter the model ID is "arcee-ai/trinity-large-thinking". It was listed on Apr 1, 2026.
How these numbers are produced
- Price and specs — provider list data from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
- Scores and ranks — LiveBench release 2026-06-25. Ranks count only models that have a published run; a blank means “not evaluated”, never “bad”.
- Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.