Can the RTX 5070 Laptop 8 GB run Mage-Flow (Microsoft)?
Download INT8 (4.2 GB). With the model's working memory it needs about 6.0 GB, leaving 2.0 GB spare on 8 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 8 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 8.2 GB | 10.0 GB | 2.0 GB too big | the original weights | Hugging Face → |
| INT8 ← SAFETENSORS · Comfy-Org | 4.2 GB | 6.0 GB | fits · 2.0 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 8 GB the FP8 encoder fits on its own, so prompt encoding stays fast.
04About this GPU
The RTX 5070 Laptop 8 GB is a Blackwell GPU with FP8 and FP4 hardware: ComfyUI computes Comfy-Org's FP8 files natively here, and NVFP4 files (where a model offers them) are faster still. As a laptop GPU it runs at a lower power limit than desktop cards (50–100 W depending on the laptop). The memory verdicts are the same; speed depends heavily on how much power the laptop maker allows.
RTX 5070 Laptop 8 GB: 8 GB GDDR7 · 128-bit · 384 GB/s · Blackwell · 50–100 W. Everything that runs on the RTX 5070 Laptop 8 GB →
05What more VRAM would change
Nothing to gain for this model: the RTX 5070 Laptop 8 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.
06Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run Mage-Flow on a RTX 5070 Laptop 8 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 5070 Laptop 8 GB?
INT8 (4.2 GB) from Comfy-Org/Mage-Flow.
Is FP8 faster than GGUF on the RTX 5070 Laptop 8 GB?
It can be. This GPU has FP8 hardware, and ComfyUI computes FP8 natively for files made for it (Comfy-Org's fp8_scaled files), or for any FP8 file with the --fast fp8_matrix_mult option. GGUF files are unpacked on the fly, which costs some speed.
How much do I need to download for Mage-Flow on the RTX 5070 Laptop 8 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 8 GB card, 32 GB of system RAM or more is recommended.