Claude 4.5 Sonnet vs GPT-5 Nano: pricing & cost comparison
On input tokens, GPT-5 Nano is the cheaper of the two — 98% less per million ($3 vs $0.05). On output, GPT-5 Nano is 97% cheaper ($15 vs $0.4) — and since output is usually the dominant cost driver, that gap matters more than it looks.
Side by side
| Claude 4.5 Sonnet | GPT-5 Nano | |
|---|---|---|
| Input / 1M tokens | $3 | $0.05 |
| Output / 1M tokens | $15 | $0.4 |
| Context window | 200,000 | 400,000 |
| Token-count accuracy | ±2% | exact |
| Cost — 10,000 input + 2,000 output tokens | $0.06 | $0.0013 |
What a real request costs
Take a representative turn — 10,000 input + 2,000 output tokens. Claude 4.5 Sonnet comes to $0.06, GPT-5 Nano to $0.0013. Across 100,000 requests that's a $5870 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.
Different leagues
These two sit in different price tiers — Claude 4.5 Sonnet runs roughly 46× the per-request cost of GPT-5 Nano on the worked example — so they rarely compete for the same job. Reach for GPT-5 Nano on high-volume, latency-sensitive work (classification, extraction, routing) and Claude 4.5 Sonnet only where the harder reasoning earns its price. They're different vendors, so expect a different API and tokenizer: the OpenAI side counts exactly; the other lands within a few percent — budget a small calibration buffer when you switch.
See the full breakdown on the dedicated pages for Claude 4.5 Sonnet and GPT-5 Nano.
FAQ
- Is Claude 4.5 Sonnet or GPT-5 Nano cheaper?
- For a typical request (10,000 input + 2,000 output tokens), GPT-5 Nano is cheaper — about 98% less, or roughly $5870 saved per 100,000 requests. Claude 4.5 Sonnet runs $3/$15 per 1M input/output tokens; GPT-5 Nano runs $0.05/$0.4.
- Which has the larger context window?
- GPT-5 Nano, at 400,000 tokens versus 200,000.
- How accurate are these token counts?
- Claude 4.5 Sonnet: Approximated with cl100k_base — drift typically <2% on English and code. 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 www.anthropic.com and openai.com, verified 2026-05-09. Vendor pricing changes often — confirm before you commit.