GPT-4o vs Claude Sonnet — reading flagship list prices honestly
Product teams often pit OpenAI’s GPT-4o class against Anthropic’s Claude Sonnet as daily-driver models for coding copilots and chat. At list prices, the winner on dollars is whichever SKU matches your median output length and tool-call depth; a small gap in output $/1M becomes a large gap when assistants emit thousands of completion tokens per task.
What to compare first
Start with output cost per 1M tokens because chat and agent loops burn completion tokens faster than most spreadsheets assume. Then compare input cost if you ship long system prompts, retrieved documents, or big diffs every turn. Finally, sanity-check context window: more capacity helps, but only if you actually fill it—otherwise you may be paying for a tier you do not use.
SKU chaos and naming
Both vendors ship multiple closely related model IDs over a year—snapshots, speed variants, and deprecation notices are normal. CloudyBot’s table uses OpenRouter-style ids from a public catalog; always confirm the exact endpoint name on your provider console before locking forecasts. If a SKU vanishes from the catalog, rerun your search on the live pricing table.
When to downgrade from flagship
If half of your traffic is classification, summarization, or short replies, a mini / flash / haiku-class lane often cuts spend more than haggling between two flagships. Route high-risk tasks to Sonnet or GPT-4o class, and bulk work to cheaper tiers—our main table’s sort and filters exist for exactly that exercise.
See also
Wider framing in OpenAI vs Anthropic and budget sorting tips in cheapest LLM API. Numbers remain list estimates, not invoices—validate on vendor billing.