Virtuoso-Small
| Property | Value |
|---|---|
| Parameter Count | 14 billion |
| License | Apache-2.0 |
| Author | Arcee.ai |
| Model URL | Hugging Face |
What is Virtuoso-Small?
Virtuoso-Small is the inaugural public release in the Virtuoso series by Arcee.ai, representing a strategic balance between computational efficiency and performance. With 14 billion parameters, it's designed to deliver enterprise-grade AI capabilities in a more accessible format, making it ideal for organizations looking to implement advanced AI solutions without requiring extensive computational resources.
Implementation Details
The model demonstrates impressive performance across various benchmarks, scoring particularly well in instruction-following tasks (79.35% on IFEval) and maintaining strong performance in complex reasoning scenarios (50.40% on BBH). Its architecture is optimized for efficient deployment while maintaining high-quality output across diverse use cases.
- Compact Architecture: 14B parameters optimized for efficient deployment
- Business-Oriented Design: Specialized for enterprise applications
- Scalable Integration: Part of broader Virtuoso ecosystem
Core Capabilities
- Advanced instruction-following with 79.35% accuracy on IFEval
- Strong reasoning capabilities demonstrated by 50.40% on BBH benchmark
- Mathematical problem-solving with 34.29% accuracy on MATH Level 5
- Professional knowledge assessment showing 46.57% on MMLU-PRO
Frequently Asked Questions
Q: What makes this model unique?
Virtuoso-Small stands out for its optimal balance between size and capability, offering enterprise-grade performance in a compact 14B parameter model. It's specifically designed for business applications while maintaining accessibility for smaller hardware configurations.
Q: What are the recommended use cases?
The model excels in customer support, content creation, and technical assistance scenarios. It's particularly well-suited for organizations requiring reliable AI capabilities without the need for extensive computational resources, while maintaining the option to scale up to larger Virtuoso models as needs grow.
