GPT-5 Mini vs GPT-5 Nano: pricing & cost comparison
On input tokens, GPT-5 Nano is the cheaper of the two — 80% less per million ($0.25 vs $0.05). On output, GPT-5 Nano is 80% cheaper ($2 vs $0.4) — and since output is usually the dominant cost driver, that gap matters more than it looks.
Side by side
| GPT-5 Mini | GPT-5 Nano | |
|---|---|---|
| Input / 1M tokens | $0.25 | $0.05 |
| Output / 1M tokens | $2 | $0.4 |
| Context window | 400,000 | 400,000 |
| Token-count accuracy | exact | exact |
| Cost — 10,000 input + 2,000 output tokens | $0.0065 | $0.0013 |
What a real request costs
Take a representative turn — 10,000 input + 2,000 output tokens. GPT-5 Mini comes to $0.0065, GPT-5 Nano to $0.0013. Across 100,000 requests that's a $520 swing in favour of GPT-5 Nano. To run the numbers on your actual prompt, paste it into the calculator and toggle Compare across all models.
Same family — pick on price
Moving between GPT-5 Mini and GPT-5 Nano is a one-line model-string change — same family, same tokenizer, nothing to re-encode. That makes this a straight cost/quality call: send the routine bulk of traffic to GPT-5 Nano ($0.05/$0.4 per 1M) and reserve GPT-5 Mini for the requests that visibly need its extra headroom. On the worked example above that split is worth about 80% per request — small per call, real money once you multiply by volume.
See the full breakdown on the dedicated pages for GPT-5 Mini and GPT-5 Nano.
FAQ
- Is GPT-5 Mini or GPT-5 Nano cheaper?
- For a typical request (10,000 input + 2,000 output tokens), GPT-5 Nano is cheaper — about 80% less, or roughly $520 saved per 100,000 requests. GPT-5 Mini runs $0.25/$2 per 1M input/output tokens; GPT-5 Nano runs $0.05/$0.4.
- Which has the larger context window?
- Both support a 400,000-token context window.
- How accurate are these token counts?
- GPT-5 Mini: Exact tokenization via the canonical OpenAI vocab (o200k_base). GPT-5 Nano: Exact tokenization via the canonical OpenAI vocab (o200k_base). The dollar math itself is exact once the token count is known.
Both prices are computed from tokenmath's verified pricing table. Rates sourced from openai.com, verified 2026-05-09. Vendor pricing changes often — confirm before you commit.