KEDA / GUIDES
How to choose between GPT, Claude, DeepSeek and Grok
Compare model quality, latency, cost and endpoint support on real tasks with a small evaluation set.
Start with the task
Define verifiable tasks such as editing code, summarizing sources, explaining mathematics or generating structured output. Compare models on the same input and record correctness, readability and format adherence, rather than relying only on names or a single leaderboard.
Consider cost, latency and features together
Check input and output token prices, context limits and support for images, tool calls and streaming. A larger model is not always necessary for every step. A lower-cost model can handle well-defined tasks while a stronger model handles complex reasoning.
Keep evaluating on your own examples
Keep a representative set of non-sensitive examples and rerun them when upgrading models or changing routes. Inspect actual usage and errors in the console. The Keda catalog lists available models; verify capabilities and results for your own tasks.