OCR Benchmarking: Maximum Accuracy at Minimum Cost

​When you take on a new visual intelligence problem, it can be hard to know which model is the right choice. Accuracy, latency, and compute cost all pull in different directions, and the largest model is not always worth what it costs. The only way to really know is to test the candidates against each other on your actual task.

​In this live session, Erik Kokalj, DevEx at Roboflow, will benchmark several models on a license plate reading task, comparing them head to head on accuracy and cost. You will see the full benchmark, including which models reached high accuracy at the lowest cost and whether an unexpected model came out on top.

​Then Erik will go behind the scenes on how the test was run. You'll get a practical look at the OpenRouter block inside a Roboflow workflow: how to add it, find the model you want, and run the same task across every candidate so the results are comparable. Roboflow runs many models natively, and the block is how you reach the ones hosted elsewhere. You'll leave able to set it up and benchmark models on your own data.

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​Every week we dive into the world of computer vision and explore new tools, interesting projects, and tutorials. This webinar is open to everyone, we hope to see you there!

We'll also make time at the end for open Q&A.