GPT-4 vs Claude Cost: How to Decide
A decision framework for choosing between GPT-4 and Claude based on real workflow token usage.
The problem
The best model is rarely the one with the cheapest per-token headline rate—it’s the one that finishes the job with fewer billed tokens.
Cost breakdown that actually matters
Compare: (1) tokens per call and (2) calls per user action. If one model needs fewer refinement passes, it can be cheaper overall even with higher rates.
A realistic example
For a drafting workflow: Model A drafts in 1 call, Model B needs 2 refinement calls. Multiply tokens by call count to see the difference.
Optimization idea (model routing)
Route tasks by complexity: cheap models for extraction/classification, premium models only for the final draft.
Guardrails
Cap retries and enforce budgets per agent so cost spikes don’t escape.