Perplexity Sonar — when search-first beats raw reasoning

Ask Claude or GPT about a news event from last week. They will either refuse (cutoff date), hallucinate (sound confident, make it up), or lean on the web search tool if you enabled it. Perplexity built their entire product around solving this. Sonar models are tuned to search first, reason over the results, and cite every claim.

Pick Sonar when

• Your answer has to be current — news, stock prices, sports scores, product launches
• You need citations the user can click
• You want one API that handles both the search and the synthesis

Stick with Claude/GPT when

• The answer is timeless (math, code, writing)
• You already enabled the lab's own web search tool and it works
• Token cost matters more than grounding quality

from openai import OpenAI

# Perplexity is OpenAI-compatible
client = OpenAI(
    api_key=os.environ["PERPLEXITY_API_KEY"],
    base_url="https://api.perplexity.ai"
)

resp = client.chat.completions.create(
    model="sonar-pro",
    messages=[{"role": "user", "content": "What were the major model releases from April 16-22, 2026?"}]
)

# The answer comes with inline citations and a 'citations' list
print(resp.choices[0].message.content)
print(resp.citations)  # array of URLs backing each claim