OpenRouter explains how to benchmark LLMs with code-graded, app-specific tasks
AIOpenRouter says LLM choices should rest on tasks drawn from an application's own inputs and output formats, graded by code. In its 60 synthetic tasks, GPT-6.1 Sol passed 180/180 trials, DeepSeek had the lowest response cost at 157/180 passes, and the public ranking agreed weakly with a Spearman correlation of 0.109.
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OpenRouter Blog · openrouter.aiPublished · added here
Original title: How to Benchmark LLMs