Choosing between the M4 MacBook Pro and the Asus ProArt laptop often depends on the specific demands of your workload. Both devices are premium options with distinct strengths, but their performance varies significantly across different tasks. This detailed analysis from Matt Talks Tech evaluates their capabilities in developer benchmarks and large language model (LLM) performance to help you make an informed decision.
Key Specifications
Understanding the core specifications of these devices is essential for assessing their performance:
- M4 MacBook Pro: Equipped with a 10-core CPU, 32GB of unified RAM, and a 1TB SSD. Its architecture is optimized for macOS, excelling in single-core performance and energy efficiency, making it a reliable choice for streamlined workflows.
- Asus ProArt: Features an AMD Ryzen 9 7940HS (12-core CPU), an RTX 4060 GPU with 8GB VRAM, 32GB of RAM, and a 1TB SSD. This configuration is designed for multitasking and GPU-intensive workloads, offering robust performance for demanding applications.
Performance in Development Workloads
JavaScript Development
For JavaScript and web development, the M4 MacBook Pro consistently outperforms the Asus ProArt. Benchmarks like Speedometer, which measure web tooling performance, highlight the MacBookβs superior execution of JavaScript tasks. Its optimized CPU and seamless macOS integration make it an excellent choice for front-end developers and web application creators who prioritize speed and efficiency.
C Programming
In C programming benchmarks, the M4 MacBook Pro demonstrates a clear advantage. It completes file creation and deletion tasks faster than the Asus ProArt, showcasing its efficiency in CPU-intensive operations. This makes it particularly suitable for developers working in low-level programming, system development, or other tasks requiring high single-core performance.
Python Scripting
Python workloads present a different scenario. The Asus ProArt edges out the M4 MacBook Pro in file creation and deletion tests, thanks to the Ryzen 9 CPUβs multi-core capabilities and slightly faster SSD write speeds. For workflows involving Python scripting, data processing, or automation tasks, the Asus ProArt offers a modest performance advantage.
Storage Speed Comparison
Both laptops feature 1TB SSDs with competitive read and write speeds. While the differences are minor, the Asus ProArt shows a slight edge in write speeds, which can be beneficial for tasks involving large data transfers or frequent file manipulations. However, for most users, the storage performance of both devices is more than sufficient for everyday development and data-handling needs.
Machine Learning Performance
CPU-Based Machine Learning
The M4 MacBook Pro excels in CPU-based machine learning tasks, achieving higher scores in Geekbench ML tests. Its strong single-core performance and efficient architecture make it a better choice for workloads that rely heavily on CPU power, such as data preprocessing, small-scale machine learning models, or algorithm testing.
GPU-Based Machine Learning
The Asus ProArt dominates GPU-based machine learning tasks. With its RTX 4060 GPU, it significantly outperforms the M4 MacBook Pro in GPU-intensive workloads, such as training deep learning models or running complex neural networks. Developers using frameworks like TensorFlow or PyTorch will find the Asus ProArtβs GPU capabilities particularly advantageous for accelerating large-scale computations.
LLM Performance
Token Generation Speed
When evaluating large language model performance, the Asus ProArt demonstrates a clear advantage in token generation benchmarks. For generating 5,000 tokens, the Asus processes 32 tokens per second compared to the MacBookβs 19.5. The gap widens with larger tasks, where the Asus achieves 58.7 tokens per second versus the MacBookβs 23.6. These results underscore the Asus ProArtβs suitability for AI workloads, particularly for developers working with LLM applications or natural language processing tasks.
Final Considerations
Your choice between the M4 MacBook Pro and the Asus ProArt ultimately depends on your specific workload and priorities:
- M4 MacBook Pro: Best suited for JavaScript development, web applications, and CPU-based machine learning tasks. Its efficiency, seamless macOS integration, and strong single-core performance make it a compelling option for front-end developers and general-purpose programming.
- Asus ProArt: Ideal for Python scripting, GPU-intensive tasks, and AI/LLM workloads. The RTX 4060 GPU provides a significant advantage for deep learning, token generation, and other GPU-accelerated applications, making it a better fit for developers working with large-scale AI models.
Both laptops deliver exceptional performance, but their strengths cater to different use cases. By aligning your choice with your specific needs, you can maximize productivity and ensure optimal performance for your projects.
Enhance your knowledge on M4 MacBook Pro by exploring a selection of articles and guides on the subject.
Source & Image Credit: Matt Talks Tech
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