Proprietary
GPT-4o is OpenAI's proven, affordable workhorse for everyday text and vision tasks. It's a legacy model now, but still a sensible default for a lot of real work.
Overview
Here's the honest version. OpenAI's frontier lineup has moved on to the GPT-5.x family, so GPT-4o is no longer the top of the range. For hard reasoning, long multi-step problems, or new frontier projects, GPT-5.4 or GPT-5.5 will serve you better.
But most business tasks aren't frontier tasks. GPT-4o still handles product copy, support replies, summaries, and reading documents well. It scored 88.7% on MMLU, and millions of production apps run on it today.
At $2.50 per million input tokens and $10 per million output, it's priced for volume. You get a 128,000-token context window and up to 16,384 output tokens per call. It reads both text and images, so document and screenshot work fits naturally.
So how do you choose? Stick with GPT-4o for simple, proven, high-volume jobs where it already works. Move to GPT-5.4 when a task needs deeper reasoning or the extra accuracy pays for itself.
It's a safe, well-understood pick — not the newest, but rarely the wrong one for mainstream work.
Real numbers
Real enterprise workloads, with the token assumptions shown openly. Your mileage varies — these are honest starting points, not guesses.
You have thousands of products and need clear descriptions for each one. GPT-4o writes them from your specs and brand style in seconds, not hours. It's accurate enough for everyday retail copy, and the low price makes bulk runs practical.
Output costs 4x more than input per token, so short, templated prompts keep bulk runs affordable.
Your support team answers the same questions all day. GPT-4o reads the customer's message plus your help articles, then drafts a reply your agent can send or edit. At high ticket volume, its low cost per reply keeps the whole thing affordable.
Most of your spend here is input — chat history plus retrieved articles — so trimming context matters more than reply length.
Finance teams still get invoices as scanned PDFs and images. GPT-4o reads each one and returns the key fields as clean data, ready for your system. Vision plus short output keeps each extraction small and low-cost to run.
Vision input with short JSON output keeps each extraction small, so cost stays low across thousands of invoices.
How we work these out: cost = (input ÷ 1M × $2.50) + (output ÷ 1M × $10.00), then × monthly volume. List prices only, no cached-input discount applied — so these are the ceiling, not the floor.
FAQ
GPT-4o costs $2.50 per million input tokens and $10.00 per million output tokens. Output is four times the price of input, so shorter responses save you money. Your real bill depends on how many tokens you send and get back each month.
Yes, for most mainstream tasks GPT-4o is still worth using in 2026. It's a legacy model now, but it's proven, affordable, and handles everyday text and vision work well. For harder reasoning or new frontier projects, move up to GPT-5.4 or GPT-5.5.
Use GPT-4o for simple, proven, high-volume work, and GPT-5.4 when the task needs deeper reasoning. GPT-4o is the older, well-understood default with low, predictable pricing. GPT-5.4 sits in OpenAI's current frontier family, so it handles complex, multi-step problems better.
GPT-4o has a 128,000-token context window. That's roughly 300 pages of text in a single request. It can return up to 16,384 tokens in one response.
GPT-4o is the more capable model, while GPT-4o mini is a smaller, lower-cost version for simpler, high-volume tasks. Pick GPT-4o when accuracy matters, like nuanced writing or reading tricky documents. Pick mini when the job is simple and you're running huge volumes where cost per request matters most.
We'll size the right model for your use case and give you a real cost estimate. One free call, no slides.
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