GPT-4 vs Sonar Pro
Sonar Pro comes out ahead, 20 to 8 on our weighted score, and it is the cheaper option too.
Sonar Pro is our pick
Sonar Pro is the better all-round choice, scoring 20/100 against GPT-4 (8). It leads on price and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceSonar ProSonar Pro $6.00 · GPT-4 $37.50 per 1M tokens (3:1 blend)
- Longest contextSonar ProSonar Pro 200,000 · GPT-4 8,192 tokens
- Widest inputsSonar ProGPT-4: Text · Sonar Pro: Text, Images
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | GPT-4 | Sonar Pro |
|---|---|---|---|
| Price | 50% | 0 | 13 |
| Inputs & features | 30% | 25 | 25 |
| Context window | 20% | 0 | 32 |
| Overall | 100% | 8/100 | 20/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification |  GPT-4OpenAI |  Sonar ProPerplexity |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $30.00 | $3.00 (best) |
| Output | $60.00 | $15.00 (best) |
| Cached input | — | — |
| Blended (3:1) | $37.50 | $6.00 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official Perplexity API |
| Limits | ||
| Context window | 8,192 tokens | 200,000 tokens (best) |
| Max output | 8,192 tokens | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | No |
| Structured output | No | No |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | gpt-4 | sonar-pro |
| API providers | 8 (best) | 5 |
| Released | Nov 6, 2023 | Jan 1, 2024 |
| Knowledge cutoff | Nov 2023 | Sep 1, 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-4$420.00
- Sonar Pro$60.00
Which should you choose?
Which is better: GPT-4 or Sonar Pro?
Sonar Pro is the better all-round choice, scoring 20/100 against GPT-4 (8). It leads on price and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GPT-4 or Sonar Pro?
Sonar Pro is cheaper at $3.00 input / $15.00 output per million tokens (official Perplexity API price). GPT-4 costs $30.00 input / $60.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $6.00 per million tokens for Sonar Pro versus $37.50 for GPT-4 (6.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GPT-4 has not been scored yet and Sonar Pro has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-4 and Sonar Pro yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Sonar Pro does not support tool calling, which most coding agents need.
Which has the bigger context window?
Sonar Pro has the largest context window at 200,000 tokens, against 8,192 for GPT-4. Maximum output per response: GPT-4 up to 8,192, Sonar Pro up to 8,192 tokens.
Which can read images, PDFs, audio or video?
GPT-4 accepts text; Sonar Pro accepts text and images. Sonar Pro handles the widest range of inputs.
Are any of these open source?
No. GPT-4 and Sonar Pro are proprietary and only available through APIs and apps.
Which is newer?
Sonar Pro is the newest, released Jan 1, 2024. GPT-4 came out Nov 6, 2023. Knowledge cutoff: GPT-4 Nov 2023, Sonar Pro Sep 1, 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
