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Introduction
OpenAI has released several models. GPT-3 started the revolution. GPT-4 improved everything. GPT-3 vs GPT-4 is a common question. Which one should you use? This post compares them side by side. You will learn the differences in size, cost, and performance.
Quick Comparison Table
| Feature | GPT-3 | GPT-4 |
|---|---|---|
| Release date | June 2020 | March 2023 |
| Parameters | 175 billion | Estimated 1.7 trillion |
| Context window | 4,096 tokens | 8,192 to 32,768 tokens |
| Multimodal | No (text only) | Yes (text + images) |
| Accuracy | Good | Significantly better |
| Cost (per 1K tokens) | ~$0.002 | ~$0.03 (15x more) |
| Best for | Budget tasks | Complex, high-stakes tasks |
For background, read GPT-3 guide.
Size and Architecture
GPT-3 has 175 billion parameters. GPT-4 is estimated at 1.7 trillion – roughly 10 times larger. More parameters mean more capacity to learn patterns.
However, OpenAI has not confirmed the exact size. They focus on performance, not specs.
For technical details on parameters, see deep learning explained.
Context Window
Context window = how much text the model can remember at once.
- GPT-3: 4,096 tokens (~3,000 words)
- GPT-4: 8,192 tokens (standard) or 32,768 tokens (extended)
With GPT-4, you can feed entire chapters of a book. GPT-3 runs out of memory faster.
Multimodal Capabilities
GPT-3 is text-only. GPT-4 can accept images as input. You show it a picture, and it describes or answers questions about it.
Example: Upload a photo of a refrigerator. Ask “What can I cook with these ingredients?” GPT-4 analyzes the image and suggests recipes.
For image generation, compare with image generation.
Performance Benchmarks
Independent tests show GPT-4 is more accurate:
- Bar exam: GPT-3 scored in bottom 10%. GPT-4 scored in top 10%.
- AP exams: GPT-4 passes most with 4s and 5s.
- Hallucinations: GPT-4 hallucinates 40% less than GPT-3.5.
For limitations of GPT-3, see GPT-3 limitations.
Cost Comparison
OpenAI charges per token. As of 2026:
| Model | Input (per 1K tokens) | Output (per 1K tokens) |
|---|---|---|
| GPT-3 (ada) | $0.0004 | $0.0004 |
| GPT-3 (davinci) | $0.02 | $0.02 |
| GPT-3.5 Turbo | $0.0015 | $0.002 |
| GPT-4 | $0.03 | $0.06 |
GPT-4 is roughly 15–30x more expensive than GPT-3.5.
When to Use GPT-3
Choose GPT-3 when:
- You have a tight budget
- Your task is simple (summarization, keyword extraction)
- You need high speed
- Accuracy is not critical
When to Use GPT-4
Choose GPT-4 when:
- Accuracy is vital (legal, medical, financial)
- You need long context (books, long reports)
- You have image inputs
- Budget allows
For specific use cases, see GPT-3 use cases.
The Middle Ground: GPT-3.5 Turbo
GPT-3.5 Turbo powers the free version of ChatGPT. It is much better than GPT-3 but cheaper than GPT-4. For many tasks, it is the best balance of cost and quality.
FAQ
1. Is GPT-3 still usable in 2026?
Yes for simple, low-cost tasks. GPT-4 is better but more expensive.
2. Can GPT-4 do everything GPT-3 can?
Yes, and more. GPT-4 is strictly better in capability.
3. Which model should a beginner use?
Start with GPT-3.5 Turbo. It is cheap and good enough for most tasks.
4. Where can I learn more?
Return to GPT-3 guide.
Conclusion
GPT-3 started the revolution. GPT-4 perfected it. GPT-4 has larger context, multimodal input, and better accuracy. However, it costs much more. Choose based on your budget and task complexity.
Next: GPT-3 limitations or GPT-3 API tutorial.
