OpenAI API Pricing 2026: GPT-4o, o3, and GPT-5 Cost Per Token Breakdown

GPT-4o costs $2.50 per million input tokens and $10 per million output in 2026; GPT-4o mini is $0.15/$0.60, and GPT-5 lands near $1.25/$10. That's the short answer. The longer answer — what a real task actually costs — is more interesting.

Headline per-token rates are the number everyone quotes and the number that matters least. What you actually pay depends on which model you route to, how many reasoning tokens it burns invisibly, whether your input is cached, and whether you run jobs in real time or in batch. Below is the full 2026 price list, then the math that turns those rates into a monthly bill.

OpenAI API Pricing 2026: The Full Per-Token Breakdown

OpenAI API pricing in 2026 spans from $0.15 per million input tokens for GPT-4o mini to $15 per million for the o1 reasoning model. GPT-4o, the default workhorse, costs $2.50 input and $10 output per million tokens. GPT-5 is priced at roughly $1.25 input and $10 output — cheaper on input than the model it replaces. You pay only for tokens processed.

Rates are per 1M tokens, USD, standard tier. OpenAI revises pricing frequently — o-series rates in particular have fallen sharply since launch. Always confirm against the live pricing page before committing a budget.

What OpenAI API Pricing Looks Like Per Real Task

A token is roughly 0.75 words, so 1,000 tokens is about 750 words. Most real requests are small — a few hundred tokens in, a few hundred out. The table below prices five common workloads on the model you'd actually pick, assuming standard (uncached) input.

*The o3 example assumes ~12K hidden reasoning tokens billed at the output rate — the single most underestimated line item in any reasoning-model budget.

The lesson: individual calls are cheap, but volume compounds fast. A product doing 5 million GPT-4o summaries a month at $0.026 each is spending $130,000 — and almost all of that is avoidable with the right routing and caching, covered below. For how this rolls up across the industry, see our AI Spending dashboard.

Why the o3 and o1 Reasoning Models Cost More

Reasoning models think before they answer, and that thinking is made of tokens you pay for. A GPT-4o answer might be 400 output tokens. The same prompt on o3 can generate 8,000–20,000 internal reasoning tokens plus the visible answer — all billed at the $8-per-million output rate. That's why o3 at a lower headline price than o1 can still cost 10–15x more than GPT-4o for the same question.

The practical rule: don't send a task to o3 unless GPT-4o or GPT-5 demonstrably fails it. Reasoning models are a scalpel, not a default. For roughly 80% of production calls, GPT-4o mini or GPT-4o is both cheaper and fast enough.

OpenAI API Pricing vs Anthropic and Google in 2026

OpenAI isn't priced in a vacuum. Anthropic's Claude and Google's Gemini set the competitive floor, and on a per-token basis the frontier tiers have largely converged near $1.25–$3 input. Here's how the flagship and budget tiers line up.

The takeaway: OpenAI is competitive-to-cheap at the flagship tier (GPT-5 matches Gemini 2.5 Pro and undercuts Claude Opus 4 by more than 10x), and GPT-4o mini is the cheapest credible general-purpose model at $0.15 input. Anthropic charges a premium for Opus-class quality. For the full competitive picture, see our OpenAI vs Anthropic enterprise breakdown.

Four Levers That Cut an OpenAI API Bill 50–70%

Stacked together, these are not marginal. A team caching a 15K-token system prompt across 2 million calls, batching its analytics jobs, and downshifting classification to GPT-4o mini routinely takes a $40,000 monthly bill under $14,000 — same product, same quality. The single highest-ROI change is usually prompt caching, because most production apps resend the same instructions on every request.