Model · Vendors

Perplexity

Ranked models from this vendor or team on Global rankings (same data snapshot as the main global board).

🇺🇸 United States

Board snapshot:

About this vendor

Perplexity offers Sonar and online-search-augmented models tuned for grounded answers with retrieval. Compare Sonar ranks, context windows, and snapshot OpenRouter pricing against other search-native chat SKUs.

🇺🇸 United States

Vendor snapshot

Catalog models 5
Ranked on Global board 1
Best rank #40
Price range (avg/1M) $1.00–$9.00/1M
Max context 200k ctx

Model types

  • Multimodal · 4
  • LLM · 1

Top ranked models

Models on this board · Global rankings

Rank Name Type Key metric 1M tokens (avg)
40 Perplexity: Sonar Pro Search Multimodal 200k ctx $9.00

Catalog models (not in ranking)

Rank Name Size Price Notes
Perplexity: Sonar 127k ctx $1.00/1M perplexity/sonar
Perplexity: Sonar Deep Research 128k ctx $5.00/1M perplexity/sonar-deep-research
Perplexity: Sonar Pro 200k ctx $9.00/1M perplexity/sonar-pro
Perplexity: Sonar Pro Search 200k ctx $9.00/1M perplexity/sonar-pro-search
Perplexity: Sonar Reasoning Pro 128k ctx $5.00/1M perplexity/sonar-reasoning-pro
Data sources & methodology

Counts and prices come from the OpenRouter catalog snapshot merged with AI Hippo Global rankings (same snapshot as /rankings/). Rank reflects the composite score on that board—not LMSYS Chatbot Arena ELO. Snapshot date: 2026-08-02. Methodology

FAQ

What is Perplexity's highest-ranked model?

Perplexity: Sonar Pro Search currently ranks #40 on AI Hippo's Global rankings board (snapshot 2026-08-02).

What does Perplexity charge per 1M tokens?

Across catalog and ranked rows, blended 1M-token prices range from $1.00 to $9.00 in the latest snapshot (2026-08-02). Check individual model pages for prompt vs completion splits.

How many Perplexity models are ranked vs catalog-only?

1 of 5 catalog models appear on Global rankings; the remaining 4 are listed under catalog-only on this page.

How is the Global rankings score calculated?

Global rankings uses on-site weighting (context window first, then blended 1M-token price)—not third-party ELO. Full methodology: /en/methodology/

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