GPU
A dedicated NVIDIA graphics card (GPU) is strongly recommended for training and applying deep learning models. Model training and applying performance on a GPU can be up to 20x faster than on a CPU, and can shorten training time from weeks to hours.
Since applying often takes seconds, compared to hours for training, a CPU can more reasonably be used if necessary. Please refer to the general System Requirements for more information on CPU requirements and recommendations.
Recommendations
Below is a table of recommended GPU options.
Specs
- Architectures: (later is better): Ada Lovelace > Ampere > Turing > Volta > Pascal
- RAM: The more the better. More important than core count. HBM2 > GDDR6X > GDDR6 > GDDR5X > GDDR5 in terms of memory bandwidth
- Cores: For a given architecture, more often leads to faster training and application times
Use Cases
- Deep Learning: Training and running deep learning models (requires 8+ GB RAM)
- Spotlight: Using Spotlight and Snap tools (requires 12+ GB RAM)
Model | Architecture | RAM | Cores | Deep Learning | Spotlight |
---|---|---|---|---|---|
NVIDIA RTX 6000 Ada | Ada Lovelace | 48 GB GDDR6 | 18176 | ✅✅✅✅ | ✅✅✅✅ |
GeForce RTX 4090 | Ada Lovelace | 24 GB GDDR6X | 16384 | ✅✅✅✅ | ✅✅✅✅ |
NVIDIA RTX 4500 Ada | Ada Lovelace | 24 GB GDDR6 | 7680 | ✅✅✅✅ | ✅✅✅✅ |
NVIDIA RTX 4000 Ada | Ada Lovelace | 20 GB GDDR6 | 6144 | ✅✅✅⚠️ | ✅✅✅⚠️ |
GeForce RTX 4080 Super | Ada Lovelace | 16 GB GDDR6X | 10240 | ✅✅✅⚠️ | ✅✅✅⚠️ |
GeForce RTX 4080 | Ada Lovelace | 16 GB GDDR6X | 9728 | ✅✅✅⚠️ | ✅✅✅⚠️ |
NVIDIA RTX 5000 Ada | Ada Lovelace | 16 GB GDDR6 | 9728 | ✅✅✅⚠️ | ✅✅✅⚠️ |
GeForce RTX 4070 Ti Super 16GB | Ada Lovelace | 16 GB GDDR6X | 8448 | ✅✅✅⚠️ | ✅✅✅⚠️ |
GeForce RTX 4070 Ti | Ada Lovelace | 12 GB GDDR6X | 7680 | ✅✅✅⚠️ | ✅✅⚠️⚠️ |
GeForce RTX 4070 Super | Ada Lovelace | 12 GB GDDR6X | 7168 | ✅✅✅⚠️ | ✅✅⚠️⚠️ |
GeForce RTX 4070 | Ada Lovelace | 12 GB GDDR6X | 5888 | ✅✅✅⚠️ | ✅✅⚠️⚠️ |
GeForce RTX 4060 Ti 16GB | Ada Lovelace | 16 GB GDDR6 | 4352 | ✅✅✅⚠️ | ✅✅⚠️⚠️ |
GeForce RTX 4060 Ti 8GB | Ada Lovelace | 8 GB GDDR6 | 4352 | ✅✅⚠️⚠️ | ✅⚠️⚠️⚠️ |
GeForce RTX 4060 | Ada Lovelace | 8 GB GDDR6 | 3072 | ✅✅⚠️⚠️ | ✅⚠️⚠️⚠️ |
NVIDIA RTX 2000 Ada | Ada Lovelace | 8 GB GDDR6 | 3072 | ✅✅⚠️⚠️ | ✅⚠️⚠️⚠️ |
NVIDIA RTX A4500 | Ampere | 20 GB GDDR6 | 7168 | ✅✅✅⚠️ | ✅✅✅⚠️ |
NVIDIA RTX A4000 | Ampere | 16 GB GDDR6 | 6144 | ✅✅✅⚠️ | ✅✅✅⚠️ |
GeForce RTX 3080 Ti | Ampere | 12 GB GDDR6X | 10240 | ✅✅✅⚠️ | ✅✅⚠️⚠️ |
GeForce RTX 3080 12GB | Ampere | 12 GB GDDR6X | 8960 | ✅✅✅⚠️ | ✅✅⚠️⚠️ |
GeForce RTX 3080 10GB | Ampere | 10 GB GDDR6X | 8704 | ✅✅⚠️⚠️ | ✅⚠️⚠️⚠️ |
GeForce RTX 3070 Ti | Ampere | 8 GB GDDR6X | 6144 | ✅✅⚠️⚠️ | ✅⚠️⚠️⚠️ |
GeForce RTX 3070 | Ampere | 8 GB GDDR6 | 5888 | ✅✅⚠️⚠️ | ✅⚠️⚠️⚠️ |
GeForce RTX 3060 | Ampere | 12 GB GDDR6 | 3584 | ✅✅✅⚠️ | ✅✅⚠️⚠️ |
Quadro RTX 6000 | Turing | 24 GB GDDR6 | 4608 | ✅✅✅✅ | ✅✅✅✅ |
Titan RTX | Turing | 24 GB GDDR6 | 4608 | ✅✅✅✅ | ✅✅✅✅ |
Quadro RTX 5000 | Turing | 16 GB GDDR6 | 3072 | ✅✅✅⚠️ | ✅✅✅⚠️ |
Quadro RTX 4000 | Turing | 8 GB GDDR6 | 2304 | ✅✅⚠️⚠️ | ✅⚠️⚠️⚠️ |
Tesla V100 32GB | Volta | 32 GB HBM2 | 5120 | ✅✅✅✅ | ✅✅✅✅ |
Tesla V100 16GB | Volta | 16 GB HBM2 | 5120 | ✅✅✅⚠️ | ✅✅✅⚠️ |
Titan V | Volta | 12 GB HBM2 | 5120 | ✅✅⚠️⚠️ | ✅✅⚠️⚠️ |
Titan Xp | Pascal | 12 GB GDDR5X | 3840 | ✅✅⚠️⚠️ | ✅✅⚠️⚠️ |
Quadro P4000 | Pascal | 8 GB GDDR5 | 1792 | ✅✅⚠️⚠️ | ✅⚠️⚠️⚠️ |
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