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Can the Mac 48 GB run Lumina Image 2.0?

Yes. 16-bit fits on the Mac 48 GB with 33.2 GB to spare.

Image model · 2.61B48 GB unified · ~40.2 GB for the GPU · 273–614 GB/s · Apple SiliconData 2026-10-01
Runs well
Yes, with room to spare.

16-bit (5.2 GB) needs about 7.0 GB in use, so 33.2 GB of the 40.2 GB stays free: room for a larger image, a LoRA or a ControlNet.

Best file16-bit
File size5.2 GB
GPU memory needed~7.0 GB
Shared memory17 / 48 GB
Memory map · Mac 48 GB7.0 GB / 40.2 GB
020 GB40 GB
Weights 16-bit · 5.2 GBWorking memory · 1.0 GBReserve · 0.8 GBFree · 33.2 GB

01What to download

PartFileFolderSize
Modellumina_2_model_bf16.safetensors
16-bit · Comfy-Org/Lumina_Image_2.0_Repackaged
models/diffusion_models5.2 GBDownload →
Text encodergemma_2_2b_fp16.safetensors
Gemma 2 2B FP16 · Comfy-Org/Lumina_Image_2.0_Repackaged
models/text_encoders5.2 GBDownload →
VAEae.safetensors
FLUX.1 VAE (ae) · Comfy-Org/Lumina_Image_2.0_Repackaged
models/vae0.3 GBDownload →
Total download · keep about the same free on disk10.8 GB

On a Mac, FP8 text encoders do not load, so a 16-bit one is listed. Sizes from Hugging Face, 2026-10-01.

Shared memory: about 16.8 GB of your 48 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 Lumina 2.0 file on 40.2 GB

FileSizeNeededOn this cardQualityDownload
16-bit ←
SAFETENSORS · Comfy-Org
5.2 GB7.0 GBfits · 33.2 GB sparethe original weightsHugging Face →
Q8_0
GGUF · calcuis
2.8 GB4.6 GBfits · 35.6 GB sparepractically identical to the originalHugging Face →
Q6_K
GGUF · calcuis
2.1 GB3.9 GBfits · 36.3 GB sparevery close to the originalHugging Face →
Q5_K_M
GGUF · calcuis
1.8 GB3.6 GBfits · 36.6 GB spareclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · calcuis
1.5 GB3.3 GBfits · 36.9 GB sparegood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · calcuis
1.1 GB2.9 GBfits · 37.3 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · calcuis
1.1 GB2.9 GBfits · 37.3 GB spareheavy loss; a last resortHugging Face →

“Needed” adds 1 GB of working memory for Lumina 2.0 and a 0.8 GB reserve. Sizes 2026-10-01.

03Measured and reported results

Nobody has sent measured numbers for this pair yet. If you run Lumina 2.0 on a Mac 48 GB, send your time per image and peak VRAM and it will appear here, credited.

04About the Mac 48 GB

A Mac with 48 GB shares that memory between the CPU and the GPU. On current macOS the GPU may use about 40.2 GB of it by default (older macOS versions: about 38.7 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 48 GB: M3 Max, M4 Pro, M4 Max, M5 Pro, M5 Max (memory bandwidth 273–614 GB/s - the higher, the faster). Everything about Macs and local AI →

48 GB unified · ~40.2 GB for the GPU · 273–614 GB/s · Apple Silicon. Everything that runs on it →

05Questions

How much VRAM does Lumina 2.0 need?

Around 2.9 GB with the smallest file (Q2_K) and 4.6 GB with an 8-bit file (Q8_0). The full 16-bit file needs about 7.0 GB.

Which Lumina 2.0 file should I download for the Mac 48 GB?

16-bit (5.2 GB) from Comfy-Org/Lumina_Image_2.0_Repackaged.

How much do I need to download for Lumina 2.0 on the Mac 48 GB?

10.8 GB: lumina_2_model_bf16.safetensors, gemma_2_2b_fp16.safetensors, ae.safetensors.