GPT-4 Turbo vs GPT-4o
The other migration off GPT-4 Turbo, without changing generation.
Side by side
| Attribute | GPT-4 Turbo | GPT-4o |
|---|---|---|
| Input, per 1M tokens | $10.00 | $2.50 |
| Output, per 1M tokens | $30.00 | $10.00 |
| Context window | 128,000 | 128,000 |
| Provider | OpenAI | OpenAI |
| Tokenizer | cl100k_base | o200k_base |
| Long-context tier | none | none |
| Retires | 2026-10-23 | no date announced |
Which to choose
- On cost, GPT-4o is 4x cheaper per million input tokens. On a workload that reads far more than it writes, that ratio is close to the whole difference in the bill.
- On capacity, both hold the same number of tokens, so neither constrains what you can send.
- On lifecycle, one of these has a retirement date and the other does not. Requests to a removed model fail outright, so this is the deciding factor regardless of price.
What this page does not tell you. Which model produces better answers. That depends on your task, and this site has no benchmark data — everything above is drawn from published pricing and specifications. Compare quality by running your own prompts through both.
Common questions
- Is GPT-4 Turbo or GPT-4o cheaper?
- GPT-4o is cheaper on input — $2.50 per million against $10.00, a difference of 4x. Output rates differ separately, and a workload heavy on generated text can reverse which one costs less overall.
- Which has the larger context window?
- Both hold 128,000 tokens, input and output combined.
- Can I compare them on my own prompt?
- Yes. The calculator counts any text against every model at once, so you can see both figures for your actual workload rather than for a generic example.
- Do I need to migrate?
- GPT-4 Turbo has a retirement date of 2026-10-23. After that the provider removes it and requests fail, so a migration is not optional — only its timing is.