| Signal | GPT-4o (2024-08-06) | Delta | Sonar Deep Research |
|---|---|---|---|
Capabilities | 67 | +17 | |
Benchmarks | 58 | +58 | |
Pricing | 10 | +2 | |
Context window size | 81 | -- | |
Recency | 23 | -39 | |
Output Capacity | 70 | +50 | |
| Overall Result | 4 wins | of 6 | 1 wins |
9
days higher
3
days
18
days higher
OpenAI
Perplexity
Sonar Deep Research saves you $150.00/month
That's $1800.00/year compared to GPT-4o (2024-08-06) at your current usage level of 100K calls/month.
| Metric | GPT-4o (2024-08-06) | Sonar Deep Research | Winner |
|---|---|---|---|
| Overall Score | 55 | 55 | -- |
| Rank | #251 | #249 | Sonar Deep Research |
| Quality Rank | #251 | #249 | Sonar Deep Research |
| Adoption Rank | #251 | #249 | Sonar Deep Research |
| Parameters | -- | -- | -- |
| Context Window | 128K | 128K | -- |
| Pricing | $2.50/$10.00/M | $2.00/$8.00/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 50 | GPT-4o (2024-08-06) |
| Benchmarks | 58 | -- | GPT-4o (2024-08-06) |
| Pricing | 10 | 8 | GPT-4o (2024-08-06) |
| Context window size | 81 | 81 | GPT-4o (2024-08-06) |
| Recency | 23 | 62 | Sonar Deep Research |
| Output Capacity | 70 | 20 | GPT-4o (2024-08-06) |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 55/100 (rank #251), placing it in the top 14% of all 290 models tracked.
Scores 55/100 (rank #249), placing it in the top 14% of all 290 models tracked.
With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Sonar Deep Research offers 20% better value per quality point. At 1M tokens/day, you'd spend $150.00/month with Sonar Deep Research vs $187.50/month with GPT-4o (2024-08-06) - a $37.50 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Sonar Deep Research also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (128K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($8.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (55/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
GPT-4o (2024-08-06) and Sonar Deep Research are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-4o (2024-08-06)
Marginally better benchmark scores; both are excellent
Best for Cost
Sonar Deep Research
20% lower pricing; better value at scale
Best for Reliability
GPT-4o (2024-08-06)
Higher uptime and faster response speeds
Best for Prototyping
GPT-4o (2024-08-06)
Stronger community support and better developer experience
Best for Production
GPT-4o (2024-08-06)
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4o (2024-08-06) | Sonar Deep Research |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Perplexity
Sonar Deep Research saves you $3.30/month
That's 20% cheaper than GPT-4o (2024-08-06) at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | GPT-4o (2024-08-06) | Sonar Deep Research |
|---|---|---|
| Context Window | 128K | 128K |
| Max Output Tokens | 16,384 | -- |
| Open Source | No | No |
| Created | Aug 6, 2024 | Mar 7, 2025 |
Both GPT-4o (2024-08-06) and Sonar Deep Research score 55/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
GPT-4o (2024-08-06) is ranked #251 and Sonar Deep Research is ranked #249 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Sonar Deep Research is cheaper at $8.00/M output tokens vs GPT-4o (2024-08-06)'s $10.00/M output tokens - 1.3x more expensive. Input token pricing: GPT-4o (2024-08-06) at $2.50/M vs Sonar Deep Research at $2.00/M.
GPT-4o (2024-08-06) has a larger context window of 128,000 tokens compared to Sonar Deep Research's 128,000 tokens. A larger context window means the model can process longer documents and conversations.