Arcee AI: Maestro Reasoning
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Arcee Maestro Reasoning is a 32-billion-parameter analytical reasoning model from Arcee AI, derived from Qwen2.5-32B and post-trained with DPO and chain-of-thought reinforcement learning to produce step-by-step logical reasoning traces.
It targets complex problem-solving, abstract reasoning, multi-step scenario modeling, and tasks requiring transparent, auditable inference chains — a natural fit for legal, financial, and scientific applications. The 128k context window allows reasoning over long documents in a single call.
On Yupp's high-reasoning benchmark, Maestro Reasoning ranks among the top five models overall, competing with significantly larger frontier models. It delivers strong reasoning quality at a mid-tier parameter count.
Context Window 131K
tokens
Max Output 32K
tokens
Input Cost $0.9
per million tokens
Output Cost $3.3
per million tokens
Release Date May 5, 2025
Code Example
Add AI to your app with the Puter.js AI API — no API keys or setup required.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms").then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms").then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
More AI Models From Arcee AI
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Trinity Large Thinking is a 398-billion-parameter sparse Mixture-of-Experts reasoning model from Arcee AI, with approximately 13B active parameters per token, post-trained with extended chain-of-thought and agentic reinforcement learning. It generates explicit reasoning traces in thinking blocks before final responses, and its 262K context window accommodates long agentic reasoning chains. Benchmark results include 94.7% on τ²-Bench and 98.2% on LiveCodeBench, placing it at #2 on PinchBench behind only Claude Opus 4.6. Released under Apache 2.0, Trinity Large Thinking is the strongest option in the Trinity family for agentic pipelines, long-horizon planning, complex multi-step coding, and tasks that benefit from transparent reasoning traces.
ChatVirtuoso Large
Arcee Virtuoso Large is a 72-billion-parameter general-purpose language model from Arcee AI, built on Qwen2.5-72B and post-trained using DeepSeek R1 distillation, multi-epoch supervised fine-tuning, and DPO/RLHF alignment. It is designed for cross-domain reasoning, enterprise question answering, creative writing, and long-document comprehension, with a 128k context window that enables processing entire codebases or lengthy documents in a single API call. Virtuoso Large is Arcee's flagship dense general-purpose model — a solid default choice for developers who need reliable, broad-capability performance without the routing complexity of MoE architectures.
Frequently Asked Questions
You can access Maestro Reasoning by Arcee AI through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Maestro Reasoning to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $0.9 |
| Output | $3.3 |
Maestro Reasoning was created by Arcee AI and released on May 5, 2025.
Maestro Reasoning supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.
Maestro Reasoning can generate up to 32K tokens in a single response.
Yes — the Maestro Reasoning API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
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