The GPT-4o Mini is a streamlined version of the GPT-4 model, designed to deliver high performance with lower computational demands.
It retains the core functionalities of GPT-4 but is optimized for efficiency, making it suitable for applications where quick response times and resource management are crucial.
Scorecard
| ✅ Availability | Yes, Try GPT-4o mini here |
| 🐙 Model Type | Large Language Model (LLM) |
| 🗓️ Release Date | July 2024 |
| 📅 Training Data Cut-off Date | October 2023 |
| 📏 Parameters (Size) | Not specified |
| 🔢 Context Window | 128k tokens |
| 🌎 Supported Languages | Multiple |
| 📈 MMLU Score | 82.0% |
| 🗝️ API Availability | Yes |
| 💰 Pricing (per 1M Token) | Input: $0.15, Output: $.60 per 1M tokens |
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Architecture 🏗️
The GPT-4o mini is a scaled-down, cost-efficient version of OpenAI's GPT-4o model. This model is designed to provide high performance while maintaining a smaller footprint, making it ideal for a range of applications where cost and efficiency are paramount.
The architecture supports both text and vision tasks, and it will eventually include support for video and audio inputs and outputs.
The context window is an impressive 128K tokens, which is significantly larger than previous models, allowing for extensive context handling.
Performance 🏎️
GPT-4o mini excels in various academic benchmarks, outperforming its predecessors and competitors in several key areas:
- Reasoning Tasks: Achieves 82.0% on MMLU, outperforming Gemini Flash (77.9%) and Claude Haiku (73.8%).
- Math and Coding Proficiency: Scores 87.0% on MGSM and 87.2% on HumanEval, surpassing Gemini Flash and Claude Haiku.
- Multimodal Reasoning: Scores 59.4% on MMMU, better than Gemini Flash (56.1%) and Claude Haiku (50.2%).
These scores highlight the model's superior ability to handle both textual intelligence and multimodal reasoning tasks.
Pricing 💵
Token Pricing
GPT-4o mini is priced at 15 cents per million input tokens and 60 cents per million output tokens. This pricing makes it significantly more affordable than previous models, including GPT-3.5 Turbo, which it outperforms in various benchmarks.
Example Cost Calculation
To provide an example, if you were to process 10 million input tokens and generate 5 million output tokens, the cost would be calculated as follows:
- Input Tokens: 10 million tokens * $0.15 per million = $1.50
- Output Tokens: 5 million tokens * $0.60 per million = $3.00
- Total Cost: $1.50 (input) + $3.00 (output) = $4.50
This cost-efficiency allows for more extensive and frequent use of the model in various applications without breaking the bank.
Use Cases 🗂️
GPT-4o mini is versatile and can be used in a wide range of applications:
- Customer Support: Fast, real-time text responses make it ideal for customer support chatbots.
- Data Processing: Efficiently handles large volumes of context, such as full code bases or conversation histories.
- APIs: Suitable for applications that chain or parallelize multiple model calls.
Customization
The model supports fine-tuning, allowing developers to adapt it to specific tasks or domains. This customization can significantly enhance the model's performance in specialized applications, making it even more versatile.
Comparison 📊
When compared to other models like Gemini Flash and Claude Haiku, GPT-4o mini stands out in multiple areas.
Its performance on reasoning tasks, math and coding proficiency, and multimodal reasoning is superior.
| Feature | GPT-4o | GPT-3.5 Turbo | GPT-4 |
|---|---|---|---|
| Launch Date | July 18, 2024 | 2021-09 | 2021-09 |
| Input Token Cost | $0.15 per million tokens | $0.5 per million tokens | $30 per million tokens |
| Output Token Cost | $0.60 per million tokens | $1.5 per million tokens | $60 per million tokens |
| Context Window | 128K tokens | 16K tokens | 8K tokens |
| Output Tokens per Request | Up to 16K tokens | Up to 4K tokens | Up to 8K tokens |
| Multimodal Capabilities | Text, Vision | Text | Text, Vision (limited) |
| Knowledge Cutoff | October 2023 | 2021 | 2021 |
| Reasoning Benchmark (MMLU) | 82% | 69.1% | 86.8% |
| Math Benchmark (MGSM) | 87.0% | 75.5% | 87.1% |
| Coding Benchmark (HumanEval) | 87.2% | 71.5% | 90.2% |
| Multimodal Reasoning Benchmark (MMMU) | 59.4% | N/A | N/A |
| Supported Languages | Same as GPT-4 | English | Multiple (same as GPT-4o) |
| API Availability | Yes | Yes | Yes |
| Latency | 2x faster than GPT-4 Turbo | Standard | Standard |
| Price | 15 cents per million input tokens, 60 cents per million output tokens | $0.5 per million input tokens, $1.5 per million output tokens | $30 per million input tokens, $60 per million output tokens |
Additionally, its cost-efficiency makes it a more attractive option for developers looking to integrate AI into their applications without incurring high expenses.
Conclusion
GPT-4o mini is a remarkable advancement in the field of AI, offering high performance at a fraction of the cost of previous models.
Its versatility and excellent performance metrics make it an ideal choice for a wide range of applications. Whether you need real-time customer support, efficient data processing, or robust API interactions, GPT-4o mini is well-equipped to meet your needs.
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