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+# Which GPU should I buy?
+
+This is a tier list of which consumer GPUs I would recommend for using with ComfyUI.
+
+In AI the most important thing is the software stack which is why this is ranked this way.
+
+# S Tier
+
+## Nvidia
+
+All Nvidia GPUs from the last 10 years (since Maxwell) are supported in pytorch and they work very well. 
+
+3000 series and above are recommended for best performance. More vram is always preferable.
+
+# B Tier
+
+## AMD (Linux)
+
+Officially supported in pytorch.
+
+Works well if the card is [officially supported](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/reference/system-requirements.html) by ROCm but they are slow compared to price equivalent Nvidia GPUs mainly because of the lack of an optimized implementation of [torch.nn.functional.scaled_dot_product_attention](https://pytorch.org/docs/stable/generated/torch.nn.functional.scaled_dot_product_attention.html) for consumer GPUs.
+
+Unsupported cards might be a real pain to get running.
+
+# C Tier
+
+## Mac with Apple silicon
+
+Officially supported in pytorch. It works but they love randomly breaking things with OS updates.
+
+## Intel (Linux + Windows)
+
+It works but it requires a custom pytorch extension and there are sometimes some weird issues.
+
+I expect things to improve over time especially once it is officially supported in pytorch.
+
+# D Tier
+
+## AMD (Windows)
+
+It requires a pytorch extension (pytorch directml) or a custom zluda pytorch build.
+
+You will have a painful experience.
+
+Things might improve in the future once they have pytorch ROCm working on windows.
+
+
+# F Tier
+
+## Qualcomm AI PC
+
+Pytorch doesn't work at all.
+
+Some quotes from someone with knowledge of the hardware and software stack: "Avoid", "Nothing works", "Worthless for any AI use"