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Compare these two on your own workload

Published rates rank differently once prompt caching, batch discounts and your own input-to-output ratio are applied. Run both against your numbers.

Claude Sonnet 5 vs GPT-5

The previous generation's general-purpose pair, for teams still running either one.

Prices verified 30 Oct 2026

OpenAI retires GPT-5 on 11 Dec 2026; the named replacement is GPT-5.6 Sol.

Input / 1M$2.00
Output / 1M$10.00
Cached input / 1M$0.200
Batch50% off
Context1.0M tokens
Blended (3:1)$4.00
Input / 1M$1.25
Output / 1M$10.00
Cached input / 1M$0.125
Batch50% off
Context400K tokens
Blended (3:1)$3.44

Monthly cost by workload shape

The same volume costs very different amounts depending on the shape of the traffic. No caching or batch applied.

WorkloadClaude Sonnet 5GPT-5Difference
Support chat
200/day · 1500 in / 300 out
$36.53$29.68GPT-5saves $6.85Model it →
RAG / search answers
20K/day · 3000 in / 400 out
$6,088.00$4,718.20GPT-5saves $1,369.80Model it →
Agent / tool-use loop
8.0K/day · 2500 in / 600 out
$2,678.72$2,222.12GPT-5saves $456.60Model it →
Batch summarization
100K/day · 5000 in / 500 out
$45.7K$34.2KGPT-5saves $11.4KModel it →
Code assistant
15K/day · 2000 in / 800 out
$5,479.20$4,794.30GPT-5saves $684.90Model it →

Frequently asked questions

Which is cheaper, Claude Sonnet 5 or GPT-5?

At a typical 3:1 input-to-output ratio, GPT-5 is cheaper: $3.44 blended per 1M tokens against $4.00. GPT-5 is cheaper at every input and output mix.

What is the price difference between Claude Sonnet 5 and GPT-5?

Claude Sonnet 5: $2.00 input, $10.00 output per 1M tokens. GPT-5: $1.25 input, $10.00 output. That is 1.6x on input and 1.0x on output.

Does prompt caching change the answer?

Claude Sonnet 5 caches input at $0.200/1M and GPT-5 caches at $0.125/1M. For input-heavy workloads with repeated context, caching can matter more than the base rate difference, model both in the calculator rather than comparing rate cards.

This page compares published prices only. It makes no claim about which model performs better on any task; that depends entirely on your evaluations.

Rate cards decide nothing on their own.

Most teams run several models at once. Finitizer Tokenomics shows what each one actually costs you, read from your own bills and exports, which workloads could test a smaller model, what they would cost on an open-weight model, and, for models you serve yourself, the cost per token beside the API price. A routing decision starts from your spend rather than a price page.

See Finitizer Tokenomics