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Can the Mac 16 GB run HunyuanImage 2.1?

Not at full quality. The 16-bit and 8-bit files are too big for the Mac 16 GB; the largest that fits is Q2_K (7.3 GB).

Image model · 17B16 GB unified · ~12.7 GB for the GPU · 68.25–200 GB/s · Apple SiliconData 2026-10-01
Tight
Only just.

Take Q2_K (7.3 GB). In use it comes to about 10.6 GB, with 2.1 GB left over on 12.7 GB. Quality: heavy loss; a last resort. For better quality, Q3_K_M (9.8 GB) also runs, with about 0.4 GB spilling into system RAM - a little slower, still practical.

Best fileQ2_K
File size7.3 GB
GPU memory needed~10.6 GB
Shared memory31 / 16 GB
Memory map · Mac 16 GB10.6 GB / 12.7 GB
06 GB13 GB
Weights Q2_K · 7.3 GBWorking memory · 2.5 GBReserve · 0.8 GBFree · 2.1 GB

01What to download

PartFileFolderSize
Modelhunyuanimage2.1-q2_k.gguf
Q2_K · calcuis/hunyuanimage-gguf
models/unet7.3 GBDownload →
Text encoderqwen_2.5_vl_7b.safetensors
Qwen2.5-VL 7B BF16 · Comfy-Org/HunyuanImage_2.1_ComfyUI
models/text_encoders16.6 GBDownload →
Text encoderbyt5_small_glyphxl_fp16.safetensors
ByT5 small Glyph-XL · Comfy-Org/HunyuanImage_2.1_ComfyUI
models/text_encoders0.4 GBDownload →
VAEhunyuan_image_2.1_vae_fp16.safetensors
HunyuanImage 2.1 VAE · Comfy-Org/HunyuanImage_2.1_ComfyUI
models/vae0.8 GBDownload →
Total download · keep about the same free on disk25.2 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 31.2 GB of your 16 GB. On this machine the model, the text encoder, the VAE and the operating system all use the same memory. That is about 15.2 GB more than there is. It still runs: while the model works, the system compresses or swaps the idle text encoder, so loading and changing the prompt get slower. A smaller file or text encoder avoids that. calculated

02Every HunyuanImage 2.1 file on 12.7 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · Comfy-Org
34.9 GB38.2 GB25.5 GB too bigthe original weightsHugging Face →
Q8_0
GGUF · calcuis
19.8 GB23.1 GB10.4 GB too bigpractically identical to the originalHugging Face →
Q6_K
GGUF · calcuis
15.7 GB19.0 GB6.3 GB too bigvery close to the originalHugging Face →
Q5_K_M
GGUF · calcuis
13.4 GB16.7 GB4.0 GB too bigclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · calcuis
11.3 GB14.6 GBspills 1.9 GBgood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · calcuis
9.8 GB13.1 GBspills 0.4 GBnoticeable loss of detailHugging Face →
Q2_K ←
GGUF · calcuis
7.3 GB10.6 GBfits · 2.1 GB spareheavy loss; a last resortHugging Face →

“Needed” adds 2.5 GB of working memory for HunyuanImage 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 HunyuanImage 2.1 on a Mac 16 GB, send your time per image and peak VRAM and it will appear here, credited.

04With more VRAM

With 24 GB you could run HunyuanImage 2.1 at 8-bit or better (Q8_0, 19.8 GB) with no offloading: for example on the RTX 4090 24 GB, RTX 3090 24 GB, RX 7900 XTX 24 GB.

05About the Mac 16 GB

A Mac with 16 GB shares that memory between the CPU and the GPU. On current macOS the GPU may use about 12.7 GB of it by default (older macOS versions: about 11.5 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 16 GB: M1, M1 Pro, M2, M2 Pro, M3, M4, M5, M6 (memory bandwidth 68.25–200 GB/s - the higher, the faster). Everything about Macs and local AI →

16 GB unified · ~12.7 GB for the GPU · 68.25–200 GB/s · Apple Silicon. Everything that runs on it →

06Questions

How much VRAM does HunyuanImage 2.1 need?

Around 10.6 GB with the smallest file (Q2_K) and 20.7 GB with an 8-bit file (FP8). The full 16-bit file needs about 38.2 GB.

Which HunyuanImage 2.1 file should I download for the Mac 16 GB?

Q2_K (7.3 GB) from calcuis/hunyuanimage-gguf. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.

FP8 or Q8_0 for HunyuanImage 2.1 on the Mac 16 GB?

Q8_0 (19.8 GB). The Mac 16 GB has no FP8 maths, so FP8 (17.4 GB) only saves memory and is a step further from the original.

How much do I need to download for HunyuanImage 2.1 on the Mac 16 GB?

25.2 GB: hunyuanimage2.1-q2_k.gguf, qwen_2.5_vl_7b.safetensors, byt5_small_glyphxl_fp16.safetensors, hunyuan_image_2.1_vae_fp16.safetensors.