From Llama to GPT-4o

A Comparative Study of Modern AI-Language Models

Introduction:

Large language models (LLMs) are rapidly evolving, with new models emerging frequently. But how do these models compare in terms of performance and cost? We recently analyzed a comprehensive benchmark comparison to find out. This article breaks down the performance of six leading LLMs across various critical tasks, giving you insights into which model might be right for your needs.

Models Tested:

Llama 3.1 70B

Llama 3.3 70B

Amazon Nova Pro

Llama 3.1 405B

Gemini Pro 1.5

GPT-4o

Categories Evaluated:

The models were put through their paces in several key areas:

General Knowledge and Reasoning: MMLU and MMLU PRO tests.

Instruction Following: Assessed with IFEval.

Code Generation: Evaluated using Human Eval and MBPP EvalPlus.

Mathematical Reasoning: Measured with the MATH benchmark.

Logical Reasoning: Tested using GPQA Diamond.

Tool Use: Measured by BFCL v2.

Long Context Handling: Assessed with NIH/Multi-needle.

Multilingual Understanding: Measured with Multilingual MGSM.

API Pricing: For 1 million input and output tokens.

Performance Breakdown:

General: Models scored similarly on MMLU (85–88 range), showing strong and comparable general knowledge. In MMLU PRO, Llama 3.3 70B and Gemini Pro 1.5 led the pack, showcasing improved reasoning skills.

Instruction Following: Llama 3.3 70B and Amazon Nova Pro were top performers, indicating better at following instructions. Gemini Pro 1.5 was noticeably weaker in this area.

Code: Amazon Nova Pro and Llama 3.1 405B showed strong performance in Human Eval, while Llama 3.3 70B edged out the others in MBPP EvalPlus.

Math: Gemini Pro 1.5 stood out with strong mathematical reasoning, leaving the rest behind. Llama 3.1 70B scored the lowest.

Reasoning: Similar to Math, Gemini Pro 1.5 performed the best, and Llama 3.1 70B the worst.

Tool Use: Llama 3.1 405B was the leader in this benchmark. GPT-4o was the lowest-performing in this category.

Long Context: Llama 3.1 70B and Llama 3.3 70B were very similar and the best in this category. Gemini Pro 1.5 was the worst.

Multilingual: Llama 3.3 70B and GPT-4o are comparable and the best, with Llama 3.1 70B scoring the lowest.

Pricing: Llama 3.1 70B and Llama 3.3 70B emerged as the most affordable, while GPT-4o was the most expensive.

Key Insights:

Llama 3.3 70B: This model shows impressive all-around performance, often topping the charts, especially in instruction following and multilingual tasks, as well as math.

Gemini Pro 1.5: Excels in math and reasoning tasks, also demonstrating a significant performance in MMLU Pro.

GPT-4o: It’s a powerful model but not consistently leading in all categories, while it is also the most expensive model.

Cost Efficiency: Llama 3.1 70B and Llama 3.3 70B are the best options when it comes to costs.

Coding Prowess: Amazon Nova Pro and Llama 3.1 405B are strong choices for coding tasks.

Conclusion:

The results of this benchmark comparison highlight that no single model is the absolute best in all areas. Your choice will depend greatly on your specific needs: math and reasoning would point to Gemini Pro 1.5, while a cost-effective, general performance would point to Llama 3.3 70B. Always balance performance against cost when making decisions about these powerful tools.

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