Claude Opus 4 vs GPT-5.5
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | Claude Opus 4 | GPT-5.5 |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Input Price (1M) | $15.00 | $5.00 |
| Output Price (1M) | $75.00 | $30.00 |
| Context Window | 200,000 | 1,000,000 |
Verdict
Claude Opus 4 costs $15.00 per 1M input tokens and $75.00 per 1M output tokens. GPT-5.5 costs $5.00 per 1M input tokens and $30.00 per 1M output tokens. GPT-5.5 is 67% cheaper on input tokens than Claude Opus 4. For output tokens, GPT-5.5 is the more affordable option at $30.00/1M vs $75.00.
On context window, GPT-5.5 supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose Claude Opus 4
- ✓ You are already integrated with Anthropic
When to choose GPT-5.5
- ✓ You need the lowest input token cost ($ 5.00/1M)
- ✓ Your workload is output-heavy — GPT-5.5 generates text cheaper
- ✓ You need a larger context window (1,000,000 tokens)
- ✓ You are already integrated with OpenAI
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is Claude Opus 4 cheaper than GPT-5.5? ▼
GPT-5.5 is cheaper on input tokens at $5.00/1M vs $15.00/1M for Claude Opus 4 — a 67% saving.
What is the context window of Claude Opus 4 vs GPT-5.5? ▼
Claude Opus 4 has a 200,000-token context window. GPT-5.5 has a 1,000,000-token context window. GPT-5.5 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: Claude Opus 4 or GPT-5.5? ▼
The best choice depends on your use case. For cost efficiency on input tokens, GPT-5.5 is the cheaper option. For maximum context length, GPT-5.5 supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.