Fireworks AI addresses the challenge of selecting the best open-source model from the rapidly expanding landscape by introducing real-world benchmarks tailored to specific tasks. Their Real-World Leaderboard evaluates models based on practical applications rather than broad academic benchmarks, enabling developers and businesses to choose the most suitable models for tasks such as customer support classification, e-commerce search, and complex agent workflows. Initial findings highlight the Qwen Instruct model's superiority in knowledge-heavy tasks, Qwen3 Coder's competitiveness for simple tool-calling scenarios, and Claude Sonnet 4's dominance in complex, multi-step reasoning tasks. Fireworks AI's approach aims to eliminate guesswork, offering model recommendations that balance proprietary and open-source options according to user preferences and task requirements.