--- title: Trinity Mini — Efficient Reasoning LLM | ModelsLab description: Run Arcee AI: Trinity Mini for 128K context reasoning and tool calling. Try the Arcee AI: Trinity Mini API for agent workflows now. url: https://modelslab.com/arcee-ai-trinity-mini canonical: https://modelslab.com/arcee-ai-trinity-mini type: website component: Seo/ModelPage generated_at: 2026-04-15T02:22:42.930507Z --- Available now on ModelsLab · Language Model Arcee AI: Trinity Mini Efficient MoE Reasoning --- [Try Arcee AI: Trinity Mini](/models/open_router/arcee-ai-trinity-mini) [API Documentation](https://docs.modelslab.com) Run Agents Seamlessly --- Sparse MoE ### 3B Active Params 26B model activates 3B per token from 128 experts for low-latency inference. Long Context ### 131K Token Window Handles extended inputs with strong utilization for grounded multi-turn responses. Tool Calling ### Reliable Function Use Delivers schema-true JSON and agent recovery in Arcee AI: Trinity Mini API. Examples See what Arcee AI: Trinity Mini can create --- Copy any prompt below and try it yourself in the [playground](/models/open_router/arcee-ai-trinity-mini). Code Review “Review this Python function for bugs and suggest optimizations: def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2)” JSON Schema “Generate valid JSON for user profile schema with name, email, age over 18, and preferences array.” Agent Workflow “Plan multi-step task: fetch weather API for NYC, compare to Tokyo, output summary in table format.” Document Summary “Summarize key points from this 10K token RAG document on quantum computing advancements.” For Developers A few lines of code. Reasoning. Few lines. --- ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed. - **Serverless:** scales to zero, scales to millions - **Pay per token,** no minimums - **Python and JavaScript SDKs,** plus REST API [API Documentation ](https://docs.modelslab.com) PythonJavaScriptcURL Copy ```

import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

``` FAQ Common questions about Arcee AI: Trinity Mini --- [Read the docs ](https://docs.modelslab.com) ### What is Arcee AI: Trinity Mini? ### How does arcee ai trinity mini work? ### What is Arcee AI: Trinity Mini API context length? ### Is Arcee AI: Trinity Mini model open-weight? ### Arcee AI: Trinity Mini alternative to what? ### Where use arcee ai trinity mini api? Ready to create? --- Start generating with Arcee AI: Trinity Mini on ModelsLab. [Try Arcee AI: Trinity Mini](/models/open_router/arcee-ai-trinity-mini) [API Documentation](https://docs.modelslab.com) --- *This markdown version is optimized for AI agents and LLMs.* **Links:** - [Website](https://modelslab.com) - [API Documentation](https://docs.modelslab.com) - [Blog](https://modelslab.com/blog) --- *Generated by ModelsLab - 2026-04-15*