# M6 Hardware Buying Guide for 2026

## 1. GPU Tiers and What They Can Run

### 8GB GPUs
- **Usage:** Suitable for basic gaming, light productivity tasks, and entry-level machine learning projects.
- **Examples:** NVIDIA GeForce GTX 1650 Super, RTX 3050 Ti.

### 12GB GPUs
- **Usage:** Ideal for intermediate gaming, professional video editing, and small-scale machine learning tasks.
- **Examples:** NVIDIA GeForce RTX 3060, RTX 3070.

### 16GB GPUs
- **Usage:** Great for high-end gaming, professional video editing, and medium-scale machine learning tasks.
- **Examples:** NVIDIA GeForce RTX 3070 Ti, RTX 3080.

### 24GB GPUs
- **Usage:** Best for professional gaming, high-end video editing, and large-scale machine learning tasks.
- **Examples:** NVIDIA GeForce RTX 3080 Ti, RTX 4080.

### 48GB GPUs
- **Usage:** Suitable for professional applications, large-scale machine learning, and video production.
- **Examples:** NVIDIA GeForce RTX 4090, RTX A6000.

### 80GB+ GPUs
- **Usage:** Best for professional-grade applications, large-scale machine learning, and high-end video production.
- **Examples:** NVIDIA GeForce RTX 5090, RTX A7000.

## 2. Specific Model Recommendations Per Tier

### 8GB
- **Recommended Models:** NVIDIA GeForce GTX 1650 Super, RTX 3050 Ti.

### 12GB
- **Recommended Models:** NVIDIA GeForce RTX 3060, RTX 3070.

### 16GB
- **Recommended Models:** NVIDIA GeForce RTX 3070 Ti, RTX 3080.

### 24GB
- **Recommended Models:** NVIDIA GeForce RTX 3080 Ti, RTX 4080.

### 48GB
- **Recommended Models:** NVIDIA GeForce RTX 4090, RTX A6000.

### 80GB+
- **Recommended Models:** NVIDIA GeForce RTX 5090, RTX A7000.

## 3. CPU vs GPU Trade-offs for Different Workloads

### Gaming
- **CPU:** Higher clock speed and cores are beneficial for gaming.
- **GPU:** Higher memory and performance are crucial for graphics-intensive games.

### Professional Video Editing
- **CPU:** Multi-core CPUs with higher clock speeds improve performance.
- **GPU:** High-performance GPUs with sufficient memory are essential.

### Machine Learning
- **CPU:** Multi-core CPUs with high clock speeds are beneficial for data preprocessing and model training.
- **GPU:** High-performance GPUs with large memory are essential for efficient model training.

## 4. Memory Requirements

- **Gaming:** 8GB RAM is minimum, 16GB is recommended for better performance.
- **Professional Video Editing:** 16GB RAM is minimum, 32GB is recommended for better performance.
- **Machine Learning:** 32GB RAM is minimum, 64GB is recommended for better performance.

## 5. Power Consumption Considerations

- **Lower Tier GPUs:** Lower power consumption, suitable for smaller systems.
- **Higher Tier GPUs:** Higher power consumption, requires more cooling and a robust power supply.

## 6. Build vs Buy Recommendations

- **Build:** Offers customization and potentially better performance, but requires technical knowledge and time.
- **Buy:** Easier and faster, but less customizable and may cost more in the long run.

## 7. Specific Product Recommendations

### RTX 4090
- **Pros:** 24GB GDDR6X memory, powerful performance for gaming and professional applications.
- **Cons:** High power consumption, expensive.

### RTX 5090
- **Pros:** 80GB GDDR6X memory, extremely powerful performance for professional applications.
- **Cons:** Very high power consumption, very expensive.

### PRO Cards
- **Pros:** Optimized for professional applications, high reliability.
- **Cons:** Expensive, not suitable for gaming.
