GPT-4.1 Pricing (per 1M tokens):
gpt-4.1
- Input: $2.00
- Cached Input: $0.50
- Output: $8.00
gpt-4.1-mini
- Input: $0.40
- Cached Input: $0.10
- Output: $1.60
gpt-4.1-nano
- Input: $0.10
- Cached Input: $0.025
- Output: $0.40
gpt-4.1
- Input: $2.00
- Cached Input: $0.50
- Output: $8.00
gpt-4.1-mini
- Input: $0.40
- Cached Input: $0.10
- Output: $1.60
gpt-4.1-nano
- Input: $0.10
- Cached Input: $0.025
- Output: $0.40
I'm not as concerned about nomenclature as other people, which I think is too often reacting to a headline as opposed to the article. But in this case, I'm not sure if I'm supposed to understand nano as categorically different than many in terms of what it means as a variation from a core model.
gpt-4o-mini for comparison:
- Input: $0.15
- Cached Input $0.075
- Output: $0.60
I was using gpt-4o-mini with batch API, which I recently replaced with mistral-small-latest batch API, which costs $0.10/$0.30 (or $0.05/$0.15 when using the batch API). I may change to 4.1-nano, but I'd have to be overwhelmed by its performance in comparision to mistral.
It's still not as notable as Claude's 1/10th the cost of raw input, but it shows OpenAI's making improvements in this area.