Anthropic's flagship model with extended thinking and xhigh effort
OpenAI's flagship, general-purpose leader
For code, agentic work, and enterprise use cases, Claude 4.7 Opus wins. For math, creative writing, and general-purpose tasks, GPT-5 wins. In production, the optimal setup is a router pattern that picks per task — yielding roughly 20% better quality and 30% cost savings.
| Category | Claude 4.7 Opus | GPT-5 |
|---|---|---|
| Performance | 10/10 | 10/10 |
| Ease of Learning | 8/10 | 9/10 |
| Ecosystem | 9/10 | 10/10 |
| Community | 9/10 | 10/10 |
| Job Market | 10/10 | 10/10 |
| Future-Proof | 10/10 | 10/10 |
from anthropic import Anthropic
client = Anthropic()
response = client.messages.create(
model="claude-opus-4-7",
extended_thinking={"enabled": True, "effort_level": "xhigh", "budget_tokens": 20000},
max_tokens=4096,
messages=[{"role": "user", "content": "Refactor this 2000-line Flask app to FastAPI"}]
)from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="gpt-5",
messages=[{"role": "user", "content": "Explain quantum entanglement"}],
reasoning_effort="high"
)For code, agentic work, and enterprise use cases, Claude 4.7 Opus wins. For math, creative writing, and general-purpose tasks, GPT-5 wins. In production, the optimal setup is a router pattern that picks per task — yielding roughly 20% better quality and 30% cost savings.
Get Free ConsultationThey're close on average across benchmarks. Claude leads on code and agentic tasks, while GPT-5 leads on math and reasoning. "Smarter" is subjective and depends on the task.