Can the RTX 2060 6 GB run Mage-Flow (Microsoft)?
Download INT8 (4.2 GB). With the model's working memory it needs about 6.0 GB, leaving 0.0 GB spare on 6 GB. Quality: practically identical to the original.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | mage_flow_int8_convrot.safetensors INT8 · Comfy-Org/Mage-Flow | models/diffusion_models | 4.2 GB | Download → |
| Text encoder | qwen3vl_4b_bf16.safetensors Qwen3-VL 4B BF16 · Comfy-Org/Mage-Flow | models/text_encoders | 8.9 GB | Download → |
| VAE | mage_flow_vae_bf16.safetensors Mage-Flow VAE · Comfy-Org/Mage-Flow | models/vae | 0.3 GB | Download → |
| Total download · keep about the same free on disk | 13.4 GB | |||
Sizes read from Hugging Face (2026-09-25). “Download” links start the file directly; the file name links are the same files the official ComfyUI workflows use.
System RAM: 32 GB or more. ComfyUI keeps the model file, the text encoder and the VAE in system RAM and moves them to the GPU as needed. With this set of files that is about 13.4 GB, plus roughly 6 GB for Windows, ComfyUI and a browser: 19.4 GB in total. With less RAM it still runs, but Windows starts swapping to disk and loading gets very slow. calculated
02Every Mage-Flow file on 6 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 8.2 GB | 10.0 GB | 4.0 GB too big | the original weights | Hugging Face → |
| INT8 ← SAFETENSORS · Comfy-Org | 4.2 GB | 6.0 GB | fits · 0.0 GB spare | practically identical to the original | Hugging Face → |
Sizes from the Hugging Face file listing, read 2026-09-25. “Needed” = file + 1 GB working memory for this model + 0.8 GB kept free for the system.
03The text encoder
Qwen3-VL 4B: 8.9 GB as 16-bit, 5.2 GB as FP8. ComfyUI encodes the prompt first and can push the encoder out of VRAM before sampling, so it does not have to fit together with the model. On 6 GB the encoder itself is too big for VRAM, so let it run from system RAM: slower prompt encoding, same images.
04About this GPU
The RTX 2060 6 GB (Turing) has no FP8 compute. FP8 files still load and save memory, but ComfyUI converts them back before the maths, so there is no speed gain — Q8_0 GGUF is the closer-to-original 8-bit choice. ComfyUI can compute INT8 files natively on NVIDIA, which is worth a try where a model offers one.
RTX 2060 6 GB: 6 GB GDDR6 · 192-bit · 336 GB/s · Turing. Everything that runs on the RTX 2060 6 GB →
05What more VRAM would change
Nothing to gain for this model: the RTX 2060 6 GB already runs a top-quality file entirely in VRAM. More memory would only help with bigger images, longer clips or several models at once.
What changes from the RTX 2060 6 GB to the RTX 3060 12 GB → · What changes from the RTX 2060 6 GB to the RTX 5060 Ti 16 GB →
06Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run Mage-Flow on a RTX 2060 6 GB, send your time per image and peak VRAM and it will appear here, credited.
07Questions
How much VRAM does Mage-Flow need?
Around 6.0 GB with the smallest file (INT8) and 6.0 GB with an 8-bit file (INT8), counting working memory and a small system reserve. The full 16-bit file needs about 10.0 GB.
Which Mage-Flow file should I download for the RTX 2060 6 GB?
INT8 (4.2 GB) from Comfy-Org/Mage-Flow.
Is FP8 faster than GGUF on the RTX 2060 6 GB?
No. This GPU has no FP8 compute, so ComfyUI converts FP8 weights back before the maths. FP8 only saves memory here; Q8_0 GGUF is the closer-to-original 8-bit pick.
How much do I need to download for Mage-Flow on the RTX 2060 6 GB?
About 13.4 GB for the model file, text encoder and VAE listed on this page, and the same again free on disk. With a 6 GB card, 32 GB of system RAM or more is recommended.