GPT-5 Nano API Pricing
OpenAI · context window 400K · prices updated 2026-09-15
Where GPT-5 Nano sits on price
At $0.4 per million output tokens, GPT-5 Nano is a budget tier model — 5.2× cheaper than the median output price of $2.08, which puts it cheaper than 84% and pricier than 16% of the models we track. It sits 9th cheapest of the 92 OpenAI models we track. Output costs 8.0× more than input here, so anything that makes the model write less — tighter instructions, structured output, lower max_tokens — moves the bill more than trimming the prompt.
Cached input is 90% cheaper. On an input-heavy workload you need roughly a 28% cache-hit rate to take 25% off the input line — reachable for chatbots and agents that resend the same system prompt and history.
What real workloads cost on GPT-5 Nano
These three workloads are the ones teams actually run on a budget-priced model — a $0.4/1M model is not bought for the same job as one ten times the price.
| Workload | Per request | Per month |
|---|---|---|
| High-volume classification — 200K requests/day (400 in / 20 out) Short output, huge volume: the input price dominates the bill. | $0 | $168 |
| Small app — 1K requests/day (500 in / 150 out) The baseline most side projects actually run at. | $0.0001 | $2.55 |
| Long-context analysis — 200 runs/day (250K in / 4K out) Only possible on large-context models; input cost is nearly the whole bill. | $0.0141 | $84.60 |
Model your exact traffic in the API cost calculator — it preloads GPT-5 Nano with caching and batch options.
GPT-5 Nano price history
GPT-5 Nano's price has not moved since we began tracking it on Aug 2, 2026 — 44 days of stability in a market where 78 of the 334 models we track have repriced over the same period, including 9 of OpenAI's own 92 models.
Change-points from our daily price snapshots (tracking since Aug 2, 2026; intraday moves between snapshots are not captured).
GPT-5 Nano vs Qwen2.5 72B Instruct
The closest-priced alternative from another vendor is Qwen2.5 72B Instruct (Alibaba (Qwen)) — priced within a rounding error on output, with $0.31 more per million input tokens. When two models land this close on price, the decision is quality on your own workload, not the price sheet: run 50 real requests through both and compare.
See Qwen2.5 72B Instruct pricing →Cheaper alternatives
More OpenAI models
Frequently asked questions
› How much does the GPT-5 Nano API cost?
GPT-5 Nano costs $0.05 per million input tokens and $0.4 per million output tokens, with cached input at $0.005 per million (90% cheaper). That works out to roughly 2,500,000 output tokens per dollar.
› What does the high-volume classification workload cost on GPT-5 Nano?
High-volume classification — 200K requests/day (400 in / 20 out) costs about $0 per request and $168 per month on GPT-5 Nano. Short output, huge volume: the input price dominates the bill.
› What does it cost to fill GPT-5 Nano's 400K context window?
Sending 400K of input in a single request costs $0.02 at $0.05 per million tokens — before any output. With prompt caching that same fill drops to about $0.002 on repeat requests. This is why large context windows are cheap to advertise and expensive to actually use.
› Is GPT-5 Nano worth the price?
GPT-5 Nano is in the cheapest end of the market — cheaper than 84% of the models we track. At this price the question is not cost but capability: it is a good fit for classification, extraction, routing and bulk summarisation, and a poor fit for multi-step reasoning where a wrong answer costs more than the tokens saved.