GPT-4o mini: How OpenAI's Latest Model Stacks Up?

OpenAI's latest offering, GPT-4o mini, marks a significant step towards affordable and accessible advanced AI. This small language model (SLM) directly challenges competitors like Llama 3 and Gemma 2, boasting low latency, cost-effectiveness, and a substantial 128K token context window. This article delves into a comprehensive evaluation of GPT-4o mini, comparing its performance against its predecessors, GPT-3.5 Turbo and GPT-4o, across a range of tasks.

Key Features and Capabilities

• Cost-Effective and Speedy: GPT-4o mini prioritizes efficiency, delivering near real-time responses at a significantly lower cost than larger models.
• Multimodal Potential: While currently supporting text and image inputs, future plans include audio and video integration.
• Exceptional Benchmark Performance: GPT-4o mini demonstrates superior performance in reasoning, math, and coding benchmarks, surpassing its predecessors and rivals.
• Wide Availability: Accessible via OpenAI's API (Assistant, Chat Completion, and Batch APIs), making advanced AI capabilities readily available to developers.

Table of Contents

• Exploring GPT-4o mini's Features
• Performance Benchmarks and Comparisons
• Pricing and Availability
• Comparative Task Analysis
• Setup and Code Examples
• Task 1: Zero-Shot Classification
• Task 2: Few-Shot Classification
• Task 3: Python Coding
• Task 4: SQL Coding
• Task 5: Information Extraction
• Task 6: Closed-Domain Question Answering
• Task 7: Open-Domain Question Answering
• Task 8: Document Summarization
• Task 9: Content Transformation
• Task 10: Language Translation
• Conclusion

Exploring GPT-4o mini's Features

OpenAI's focus on affordability is evident in GPT-4o mini's design. Its low cost and latency facilitate rapid development of generative AI applications. The large context window enables processing of extensive text data, resulting in quick responses and efficient parallelization of API calls.

Like GPT-4o, GPT-4o mini is multimodal, currently handling text and images, with future support for audio and video. Trained on data up to October 2023, it boasts a 128K token input context window and a 16K token output limit per request. Sharing the same tokenizer as GPT-4o, it offers improved performance for non-English prompts.

Performance Benchmarks and Comparisons

Rigorous testing against various LLMs, including Gemini, Claude, GPT-3.5 Turbo, and GPT-4o, reveals GPT-4o mini's superior performance.

Key benchmark results highlight GPT-4o mini's strengths:

• Reasoning: Scores of 82.0% on MMLU, exceeding Gemini Flash (77.9%) and Claude Haiku (73.8%).
• Mathematics: Achieves 87.0% on MGSM, surpassing Gemini Flash (75.5%) and Claude Haiku (71.7%).
• Coding: Scores 87.2% on HumanEval, outperforming Gemini Flash (71.5%) and Claude Haiku (75.9%).
• Multimodal Reasoning: Strong performance on MMMU with a score of 59.4%, compared to 56.1% for Gemini Flash and 50.2% for Claude Haiku.

Independent analysis by Artificial Analysis further validates GPT-4o mini's speed and cost advantages.

GPT-4o mini also excels in function and tool calling, making it suitable for complex AI agent development. Its improved long-context performance and ability to extract structured data and generate high-quality email responses are notable advantages.

Pricing and Availability

GPT-4o mini is readily available through OpenAI's Assistant, Chat Completion, and Batch APIs. The pricing is highly competitive: \$0.15 per 1M input tokens and \$0.60 per 1M output tokens. Access via ChatGPT (Free, Plus, and Team plans) is also expected soon.

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