Select an endpoint and copy a working example for this model.
from openai import OpenAI client = OpenAI( api_key="YOUR_API_KEY", base_url="https://api.apertis.ai/v1") response = client.chat.completions.create( model="sonar-pro", messages=[ {"role": "user", "content": "Hello!"} ], max_tokens=1024, temperature=0.7) print(response.choices[0].message.content) # Optional: Enable context compression to reduce token usage# response = client.chat.completions.create(# model="sonar-pro",# messages=[{"role": "user", "content": "Hello!"}],# extra_body={"compression": {"enabled": True, "model": "gpt-4.1-mini"}}# )modelmessagesmax_tokenstemperaturetop_pstreamtoolsreasoning_effortstream_optionsthinkingextra_bodyUse these namespaced identifiers in Cursor IDE to avoid conflicts with built-in models.
See how this model compares to others from the same provider.
Sonar Pro Search is Perplexity's most advanced agentic search system, available only via OpenRouter. It powers the Pro Search mode on Perplexity, adding autonomous multi-step research workflows instead of single-query answers. Pricing combines token costs with a per-request fee.
See how this model compares to others from the same provider.
Sonar Pro Search is Perplexity's most advanced agentic search system, available only via OpenRouter. It powers the Pro Search mode on Perplexity, adding autonomous multi-step research workflows instead of single-query answers. Pricing combines token costs with a per-request fee.
No observed failures in the current observation window