Sonar Deep Research
Specialized model for comprehensive research and deep information analysis.
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Popularity trends show adoption over time
Rising popularity indicates growing trust; declines may signal newer alternatives
- •Popular = trusted by many builders for everyday tasks
- •Try a cheaper model on your prompt—if outputs match, save money
- •After adding Actions or tools, test again—costs can change a lot
Popularity Trend
Current popularity ranking
Compare cost against similar models
Use cheaper alternatives to validate if premium pricing is worth it
- •Test your prompt on cheaper models—if outputs match, save money
- •Premium models shine at complex reasoning or long-context tasks
- •After adding Actions or tools, check costs again—they can change a lot
Cost Comparison
Model vs Perplexity average and nearby models
Compare within the same provider
Use cheaper or pricier neighbors to decide if the premium is justified
- •If outputs match on your prompt, pick the cheaper one
- •Premium models excel at specific things like reasoning or long context
- •Test again after adding Actions—costs and quality can change
Provider Popularity Split
Top peers in Perplexity by total uses (higher = more popular)
Token usage shows typical workload patterns
Most runs use 1-5k tokens for conversations; higher counts indicate complex prompts or RAG
- •Low tokens = quick responses; high tokens = detailed analysis or RAG
- •Compare input/output to see if this model handles quick or long tasks
- •Shorter prompts = lower costs—test variations in Pickaxe
Token Usage Distribution
Most requests use 25k-50k tokens
Usage trends reflect adoption and trust
Growing trends indicate increasing adoption; declines may signal migration to alternatives
- •Rising usage = builders trust this model for real work
- •Spikes often mean new features, use cases, or promotions
- •If trends drop, try newer or cheaper alternatives in Pickaxe
Market Share Distribution— Rank #31 of 53
This model's market share compared to all models• 0.21% market share
Speed metrics show real-world response times
Latency affects user experience; lower latency means faster interactions
- •Average = typical response time; worst case = slowest 5% of requests
- •First response time = how fast users see something
- •Compare speed across models in Pickaxe to find the best balance
Performance
Response time and streaming metrics
Real builder experiences
Was this model actually good in Pickaxe?
Share wins, failures, and cost/performance tradeoffs with other builders. The more real-world runs, the better the guidance.
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