GPT vs Claude pricing
AI API Pricing Comparison
Compare OpenAI and Anthropic API pricing by input tokens, cached input tokens, output tokens, and production request volume. Use this page to evaluate GPT vs Claude cost before choosing a model.
OpenAI pricing rule
GPT-5.4 Mini Token Cost Calculator
Estimated API cost
$0.06- Input
- $0.0375
- Cached input
- $0.00
- Output
- $0.0225
- Per 1,000 requests
- $60.00
Cost Per Million Tokens
| Model | Input | Cached input | Output | Context |
|---|---|---|---|---|
| GPT-5.5 | $5 | $0.5 | $30 | Provider dependent |
| GPT-5.4 | $2.5 | $0.25 | $15 | Provider dependent |
| GPT-5.4 Mini | $0.75 | $0.075 | $4.5 | Provider dependent |
| Claude Sonnet 4 | $3 | $0.3 | $15 | 200,000 tokens |
| Claude Opus 4 | $15 | $1.5 | $75 | 200,000 tokens |
| Claude Haiku 3.5 | $0.8 | $0.08 | $4 | 200,000 tokens |
GPT vs Claude Pricing Snapshot
How To Compare AI API Pricing
Start with the real token pattern of your workflow. A chatbot might have short input and moderate output. A RAG workflow often has large input because retrieved chunks are included. An agent may run several model calls for one user task.
After estimating one request, scale the result to 1,000 requests and then to monthly traffic. That exposes costs that are invisible when you only compare per-million-token rates.
Best Comparison Signals
- Input token price for RAG and long context
- Output token price for writing and coding
- Cached-input price for repeated prompts
- Average model calls per workflow
- Retry rate and quality requirements
Cheapest AI API Is Workflow-Dependent
A model with the lowest input price is not always the cheapest overall. If your workload generates long answers, output pricing matters more. If your agent retries often, reliability and task completion rate can matter more than the listed token price.
Pricing sources: OpenAI and Anthropic. Estimates are intended for planning and SEO research, not invoice reconciliation.
FAQ
What is the cheapest AI API?
The cheapest AI API depends on token mix. Input-heavy RAG workloads should compare input and cached-input pricing, while writing and coding workloads should compare output pricing.
Is GPT cheaper than Claude?
Sometimes. GPT and Claude pricing varies by model tier, input tokens, output tokens, cache behavior, and the number of model calls needed to complete a task.
Why compare cached input pricing?
Cached input pricing matters when the same prompt prefix, policy, schema, or context is reused across many requests. It can materially reduce repeated-context workloads.
How do I compare AI API cost for agents?
Estimate cost per model call, then multiply by average agent steps per task. A model with higher token pricing can be cheaper if it finishes tasks with fewer retries.
What should I compare before choosing an AI model?
Compare input price, output price, cached-input price, context requirements, expected retries, latency needs, and quality requirements for your workflow.