Measure cost, time, and quality of key AI models on real-world business tasks
Austin, Texas, May 13, 2026 /PRNewswire/ — Today, May 13, 2026 Orufuro released ORCFLO indexis a unique benchmark that evaluates leading AI models on common business tasks such as analysis, writing, and summarization. Unlike existing AI benchmarks designed for computer scientists, the ORCFLO index measures the work that knowledge workers actually do. The ORCFLO Index measures the performance of frontier models in terms of cost, time, and quality, empowering business users to choose evidence-based AI models.
Today’s AI benchmarks were built by AI researchers for graduate-level AI researchers in areas such as reasoning, code generation, and math problem solving. While useful for academic research, it cannot tell corporate buyers which model produces better board summaries or extracts cleaner structured data from regulatory filings. The ORCFLO index provides new transparency to businesspeople into the models of major frontier vendors such as OpenAI, Anthropic, and Google.
of ORCFLO index measures each AI model in three general areas: ability (What you can do with the model, such as analysis, summarization, structured extraction, etc.) action (how the model follows instructions and maintains style consistency), and stability (How reliably the model performs across runs and edge cases). Each model is given a series of 40+ detailed test cases, and the output is judged by a multi-judge AI panel using a rigorous true/false rubric.
Although the methodology is published on the ORCFLO website, the specific test prompts and rubrics for operationalizing the methodology are proprietary. The index is vendor agnostic and evaluates leading AI models from major frontier vendors. We do not give preferential treatment to vendors.
For example, the Analytics category has specific test cases to determine whether an AI model can identify disqualifying factors before addressing superficial questions. That is, it detects trick questions and queries that are based on false assumptions. Other test cases include condensing a 30-page strategy memo into a summary and extracting structured data from a quarterly financial report. Model results are evaluated based on rigorous criteria to ensure that all models from all vendors are treated fairly.
“There is no single best AI model. There is just a model that is best suited for the task you are performing, depending on the constraints you are operating under. Historical AI benchmarks were not built for businessmen and therefore to evaluate models in business terms. The ORCFLO Index provides the facts you need to answer the right question: What is the best model for this task?” said Brian Walker, co-founder and CEO of ORCFLO.
