AI · 2h ago
Why per-token pricing misleads AI cost comparisons
Jan Ilowski argues that comparing AI model costs per million tokens ignores crucial factors like output structure and caching. He shows that models with higher per-token prices can be cheaper for real tasks due to shorter outputs. Developers should evaluate total cost per task, not just token rates.
Meridian48 take
The piece rightly calls out a common oversimplification, but the real challenge is that task-level benchmarking is harder to standardize than token counts.
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