metadata
license: apache-2.0
base_model:
- Qwen/Qwen2.5-14B
Virtuoso-Small
Virtuoso-Small is the debut public release of the Virtuoso series of models by Arcee.ai, designed to bring cutting-edge generative AI capabilities to organizations and developers in a compact, efficient form. With 14 billion parameters, Virtuoso-Small is an accessible entry point for high-quality instruction-following, complex reasoning, and business-oriented generative AI tasks. Its larger siblings, Virtuoso-Forte and Virtuoso-Prime, offer even greater capabilities and are available via API at models.arcee.ai.
Performance Benchmarks
| Groups | Metric | ↑ | Value | ± | Stderr |
|---|---|---|---|---|---|
| Leaderboard | Accuracy | ↑ | 0.5194 | ± | 0.0046 |
| Normalized Accuracy | ↑ | 0.5814 | ± | 0.0051 | |
| Exact Match | ↑ | 0.3006 | ± | 0.0117 | |
| Instruction-Level Loose Accuracy | ↑ | 0.8489 | ± | N/A | |
| Instruction-Level Strict Accuracy | ↑ | 0.8249 | ± | N/A | |
| Prompt-Level Loose Accuracy | ↑ | 0.7856 | ± | 0.0177 | |
| Prompt-Level Strict Accuracy | ↑ | 0.7523 | ± | 0.0186 | |
| Leaderboard-BBH | Normalized Accuracy | ↑ | 0.6516 | ± | 0.0058 |
| Leaderboard-GPQA | Normalized Accuracy | ↑ | 0.3389 | ± | 0.0137 |
| Leaderboard-Math-Hard | Exact Match | ↑ | 0.3006 | ± | 0.0117 |
| Leaderboard-MuSR | Normalized Accuracy | ↑ | 0.4286 | ± | 0.0175 |
Key Features
- Compact and Efficient: With 14 billion parameters, Virtuoso-Small provides a high-performance solution optimized for smaller hardware configurations without sacrificing quality.
- Business-Oriented: Tailored for use cases such as customer support, content creation, and technical assistance, Virtuoso-Small meets the demands of modern enterprises.
- Scalable Ecosystem: Part of the Virtuoso series, Virtuoso-Small is fully interoperable with its larger siblings, Forte and Prime, enabling seamless scaling as your needs grow.
Deployment Options
Virtuoso-Small is available under the Apache-2.0 license and can be deployed locally or accessed through an API at models.arcee.ai. For larger-scale or more demanding applications, consider Virtuoso-Forte or Virtuoso-Prime.