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By tokenmath Research Desk · Pricing verified 2026-05-09

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 SonnetGPT-5 Nano
Input / 1M tokens$3$0.05
Output / 1M tokens$15$0.4
Context window200,000400,000
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.

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