NVIDIA GeForce RTX 4090 vs NVIDIA GeForce RTX 4080 SUPER
Side-by-side comparison for AI and gaming. Which one should you buy in 2026?
Bottom Line
NVIDIA GeForce RTX 4090 has more VRAM (24GB vs 16GB) but costs more ($1400 vs $950). For AI, the extra VRAM is usually worth it — larger models mean smarter responses. For gaming only, NVIDIA GeForce RTX 4080 SUPER may be the better value.
AI Model Compatibility
How each GPU handles popular AI models. VRAM determines whether a model fits — green means it runs, red means it won't.
Estimated Performance (tok/s)
Bandwidth-based estimates, not hardware benchmarks. Methodology
NVIDIA GeForce RTX 4090
The RTX 4090 remains the gold standard for local AI in 2026. Its 24GB of GDDR6X VRAM hits the professional sweet spot — running 32B parameter models at Q8 quality and Llama 70B at Q4 quantization. Despite being a previous-generation card, it is still one of the fastest gaming GPUs available and has the most mature driver and software ecosystem. Used 4090s represent the best value proposition for serious AI builders.
Full specs →NVIDIA GeForce RTX 4080 SUPER
The RTX 4080 SUPER delivers excellent 4K gaming performance with 16GB of GDDR6X memory. It is a strong card for gaming-first builds that want some AI capability. The 16GB VRAM handles 14B models at Q4 and runs Stable Diffusion XL comfortably. However, for dedicated AI builds, the 4090's 24GB offers significantly more headroom for the price difference.
Full specs →Who Should Buy Which?
Buy the NVIDIA GeForce RTX 4090 if:
- + You need 24GB VRAM for larger AI models
- + AI workloads are your primary use case
- + You want better gaming performance
- + The all-rounder — serious AI inference + top-tier gaming
Buy the NVIDIA GeForce RTX 4080 SUPER if:
- + You want to save $450
- + You want lower power consumption (320W vs 450W)
- + Premium 4K gaming with moderate AI capability