Can the Mac 128 GB run Qwen-Image 2.1?
Yes. 16-bit fits on the Mac 128 GB with 98.9 GB to spare.
16-bit (14.2 GB) needs about 16.5 GB in use, so 98.9 GB of the 115.4 GB stays free: room for a larger image, a LoRA or a ControlNet.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | qwen_image_2.1_bf16.safetensors 16-bit · Comfy-Org/Qwen-Image-2.1 | models/diffusion_models | 14.2 GB | Download → |
| Text encoder | qwen3vl_8b_bf16.safetensors Qwen3-VL 8B BF16 · Comfy-Org/Qwen-Image-2.1 | models/text_encoders | 17.5 GB | Download → |
| VAE | qwen_image_2.1_vae_bf16.safetensors Qwen-Image 2.1 VAE · Comfy-Org/Qwen-Image-2.1 | models/vae | 0.7 GB | Download → |
| Total download · keep about the same free on disk | 32.4 GB | |||
On a Mac, FP8 text encoders do not load, so a 16-bit one is listed. Sizes from Hugging Face, 2026-10-01.
Free ComfyUI workflow, tested on my RTX 5060 Ti: INT8 workflow (.json). Drag the file into ComfyUI. All workflows →
Shared memory: about 38.4 GB of your 128 GB. On this machine the model, the text encoder, the VAE and the operating system all use the same memory. That leaves room, so nothing has to be swapped to disk. calculated
02Every Qwen-Image 2.1 file on 115.4 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit ← SAFETENSORS · Comfy-Org | 14.2 GB | 16.5 GB | fits · 98.9 GB spare | the original weights | Hugging Face → |
| Q8_0 GGUF · Abiray | 7.6 GB | 9.9 GB | fits · 105.5 GB spare | practically identical to the original | Hugging Face → |
| Q6_K GGUF · Abiray | 5.9 GB | 8.2 GB | fits · 107.2 GB spare | very close to the original | Hugging Face → |
| Q5_K_M GGUF · Abiray | 5.0 GB | 7.3 GB | fits · 108.1 GB spare | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · Abiray | 4.2 GB | 6.5 GB | fits · 108.9 GB spare | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · Abiray | 3.2 GB | 5.5 GB | fits · 109.9 GB spare | noticeable loss of detail | Hugging Face → |
“Needed” adds 1.5 GB of working memory for Qwen-Image 2.1 and a 0.8 GB reserve. Sizes 2026-10-01. FP8 and INT8 files are left out on a Mac: Apple GPUs cannot compute FP8, so ComfyUI either fails to load them or converts them back to 16-bit, which saves no memory. Use a 16-bit or GGUF file.
03Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run Qwen-Image 2.1 on a Mac 128 GB, send your time per image and peak VRAM and it will appear here, credited.
04About the Mac 128 GB
A Mac with 128 GB shares that memory between the CPU and the GPU. On current macOS the GPU may use about 115.4 GB of it by default (older macOS versions: about 103.1 GB); that is the figure used here. ComfyUI can go past it, but macOS then starts compressing and swapping memory and everything slows down. ComfyUI runs on Apple GPUs through PyTorch's MPS backend. 16-bit and GGUF files work; FP8 and INT8 files do not save memory on a Mac, so they are skipped. Speed is the catch: even the fastest Macs are several times slower per image than a desktop RTX card. Chips sold with 128 GB: M1 Ultra, M2 Ultra, M3 Max, M4 Max, M5 Max (memory bandwidth 300–800 GB/s - the higher, the faster). Everything about Macs and local AI →
128 GB unified · ~115.4 GB for the GPU · 300–800 GB/s · Apple Silicon. Everything that runs on it →
05Questions
How much VRAM does Qwen-Image 2.1 need?
Around 5.5 GB with the smallest file (Q3_K_M) and 9.6 GB with an 8-bit file (INT8). The full 16-bit file needs about 16.5 GB.
Which Qwen-Image 2.1 file should I download for the Mac 128 GB?
16-bit (14.2 GB) from Comfy-Org/Qwen-Image-2.1.
How much do I need to download for Qwen-Image 2.1 on the Mac 128 GB?
32.4 GB: qwen_image_2.1_bf16.safetensors, qwen3vl_8b_bf16.safetensors, qwen_image_2.1_vae_bf16.safetensors.