Claude Opus 4.7 vs GPT-5
The two top-tier reasoning models, head-to-head on price, context, and benchmark performance.
Claude Opus 4.7 and GPT-5 are the most capable LLMs available as of 2026. Pricing is similar; context window favors Claude (1M vs 256k). Benchmark wins are split: Claude excels at long-context analysis, code, and structured agentic work; GPT-5 excels at multimodal reasoning (image+text) and creative tasks. For most production workloads, the better choice is the one your existing infrastructure already supports.
Key Differences
| Aspect | Claude Opus 4.7 Cost Calculator | GPT-5 API Cost Calculator |
|---|---|---|
| Input price | $15/MTok | ~$10/MTok |
| Output price | $75/MTok | ~$30/MTok |
| Context window | 1M tokens | 256k tokens |
| Multimodal | Image input, text output | Image, audio, video |
| Tool use / agentic | Excellent | Excellent |
| Prompt caching | Yes (90% off) | Yes (50% off) |
When to use Claude Opus 4.7 Cost Calculator
- Long-context tasks (analyze a whole codebase or book)
- Tool use and agentic workflows
- Code generation and refactoring
- You're using Claude Agent SDK or Anthropic SDK
When to use GPT-5 API Cost Calculator
- Multimodal (image + text) inputs
- Creative writing and ideation
- You're using OpenAI Assistants/Function Calling
- OpenAI ecosystem dependencies
Frequently Asked Questions
Which is "smarter"?
Roughly equivalent on most public benchmarks. Each has strengths: Claude on code and long context; GPT-5 on math reasoning and multimodal. Run your own evals on your specific task before committing.
Should I switch from one to the other?
Probably not for cost — pricing is similar. Switch if you need a specific capability (e.g., 1M context, or audio). Most production teams use both, routing tasks to whichever performs best per workload.