GPT-4o Mini Pricing Guide (March 2026): The Cheapest OpenAI Model Worth Using
GPT-4o mini costs $0.15 per million input tokens and $0.60 per million output tokens. That is 16× cheaper on input than GPT-4o ($2.50/M) and about the same as Gemini 2.5 Flash — currently the most affordable tier from either provider.
It is also one of the most underused models in production. Many teams default to GPT-4o or GPT-4.1 end-to-end, when a large portion of their workload — classification, extraction, simple summarisation — would run correctly on mini at a fraction of the cost. If you have not benchmarked mini on your actual prompts, that is the most valuable experiment you can run this week.
What GPT-4o mini actually costs at scale
At 1,000 requests per day averaging 500 input and 500 output tokens: GPT-4o mini runs roughly $0.23/day, or $6.75/month. The same workload on GPT-4o costs $4.50/day, or $135/month. That is a 20× difference at moderate volume.
At 100,000 requests per day — a common production scale for classification or extraction pipelines — GPT-4o mini costs roughly $675/month. GPT-4o at the same volume: approximately $13,500/month. At that scale, model routing pays for itself in the first day of the month.
What GPT-4o mini handles well
GPT-4o mini reliably handles structured, well-defined tasks: text classification (ticket routing, intent detection, sentiment labelling), data extraction and transformation, short summarisation of structured or semi-structured content, simple question-answering within a defined domain, output formatting, and translation. For any task where the input is clearly defined and the output format is constrained, mini is the right starting point.
Its limitations appear on complex multi-step reasoning, long-form synthesis across many documents, tasks requiring sustained coherence over very long outputs, and nuanced creative work. For those, a flagship model is appropriate. For everything else, benchmark mini first.
GPT-4o mini vs Claude Haiku 4.5 vs Gemini 2.5 Flash
All three providers have a budget tier. GPT-4o mini: $0.15/1M input, $0.60/1M output. Gemini 2.5 Flash: $0.30/1M input, $2.50/1M output. Claude Haiku 4.5: $1.00/1M input, $5.00/1M output.
GPT-4o mini is the cheapest at the budget tier. Gemini 2.5 Flash costs about 2× more on input and 4× more on output. Claude Haiku 4.5 is about 6–7× more expensive than GPT-4o mini. If you are on Anthropic and not using Haiku for volume tasks, the savings from downtiering from Sonnet are substantial. If you are choosing between OpenAI and Google at the budget tier, GPT-4o mini wins on price; Gemini 2.5 Flash offers a larger context window (1M tokens) if that matters for your use case.
The routing question that matters most
Most products have multiple AI features, not one. A chatbot, an email classifier, a document summariser, an extraction pipeline. Each has different complexity requirements. Running all of them on a flagship model is the most common source of preventable AI spend.
The routing approach: identify your highest-volume features, test them on mini, deploy the switch where quality holds. For most teams, this cuts the API bill by 40–60%. The hard part is knowing which features and customers are driving the current spend before you start making changes. That is what PerUnit is built for — cost by feature, customer, and pricing tier. Or run the side-by-side comparison now with our free model cost comparison tool.