# Trinity Nano Preview Usage, Cost & Rank | OpenCode Data

Experimental chat-tuned 6B MoE model with 1B active parameters for low-resource chat and instruction following

- Page: https://opencode.ai/data/arcee-ai/trinity-nano-preview
- JSON: https://opencode.ai/data/arcee-ai/trinity-nano-preview.json
- Model ID: arcee-ai/trinity-nano-preview
- Lab: Arcee AI

## Model facts

| Fact | Value |
| --- | --- |
| Context window | 131K |
| Max output | 131K |
| Knowledge cutoff | - |
| Release date | 2025-12-01 |
| Input modalities | text |
| Output modalities | text |
| Reasoning | No |
| Tool calling | Yes |
| Open weights | Yes |
| Weights | [Hugging Face](https://huggingface.co/arcee-ai/Trinity-Nano-Preview) |

## Methodology

- Updates: Aggregated every hour. Days and weeks use UTC.
- Tokens: Input, output, reasoning, and cached tokens for each request.
- Users and sessions: Approximate counts of distinct users and OpenCode sessions.
- Cost: Session cost is the average cost per OpenCode session. Token prices are list prices from the OpenCode model catalog.
- Retention: The share of a model's users in one week who use it again the next week.
- Citation: Cite OpenCode Data (opencode.ai/data) with the update time shown at the top of the page.