Best NVIDIA GPUs in 2026
Best GPUs under CA$400 for everyday use
No GPUs under CA$700 yet. See our top picks under CA$1,000
Best GPUs under CA$1,000 for everyday use
NVIDIA 900-5G172-2580-000
Best GPUs under CA$1,500 for everyday use
NVIDIA GeForce RTX 3080 10GB GDDR6X
Great Alternatives
These options also score highly and may better suit your specific needs
NVIDIA Quadro RTX 5000 16GB GDDR6 workstation
Premium GPUs for everyday use
NVIDIA 900-1G144-2545-000
Great Alternatives
These options also score highly and may better suit your specific needs
NVIDIA 900-5G132-2540-000
NVIDIA 9001G1362505000
NVIDIA GeForce RTX 4070 Founders Edition 12GB GDDR6X
Why we recommend this ▼
The Ada Lovelace architecture and DLSS 3 frame generation deliver a substantial 1440p performance leap over the previous generation, all within a compact 244mm dual-slot design and a 200W power envelope. The Founders Edition cooler maintains quiet operation while the 12GB GDDR6X memory buffer handles high-resolution textures effectively. This card is best for 1440p gamers seeking a power-efficient upgrade that fits easily into small form factor builds.
NVIDIA RTX PRO 6000 Blackwell Server Edition 96GB GDDR7 workstation
NVIDIA GeForce RTX 3060 Ti 30 Series 8GB GDDR6
Why we recommend this ▼
The Ampere-based RTX 3060 Ti delivers strong 1080p and capable 1440p gaming via 4864 CUDA cores and 8GB of 256-bit GDDR6 memory. Its compact dual-fan, 2-slot design at 242mm fits easily into smaller builds while still supporting ray tracing and DLSS. This card is best for 1080p gamers wanting high refresh rates in a power-efficient 200W package.
NVIDIA Blackwell GPU Jetson Thor 128GB workstation
Why we recommend this ▼
Equipped with a 2560-core NVIDIA Blackwell GPU and 96 fifth-gen Tensor Cores, this developer kit delivers 2070 TFLOPS of AI performance for demanding model training. The 128GB memory pool and dedicated AI acceleration make it a specialized tool for edge computing and robotics prototyping. This kit is best for AI researchers and robotics engineers developing and deploying large language models directly on-device.
