Can the Mac 16 GB run Krea 2 (Turbo)?
Not at full quality. The 16-bit and 8-bit files are too big for the Mac 16 GB; the largest that fits is Q5_K_M (8.9 GB).
Q5_K_M (8.9 GB) fits with only 1.2 GB to spare (about 11.5 GB of 12.7 GB). Quality: close; small differences in fine detail. For better quality, Q6_K (10.6 GB) also runs, with about 0.5 GB spilling into system RAM - a little slower, still practical.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | krea2_turbo-Q5_K_M.gguf Q5_K_M · vantagewithai/Krea-2-Turbo-GGUF | models/unet | 8.9 GB | Download → |
| Text encoder | qwen3vl_4b_bf16.safetensors Qwen3-VL 4B BF16 · Comfy-Org/Krea-2 | models/text_encoders | 8.9 GB | Download → |
| VAE | qwen_image_vae.safetensors Qwen-Image VAE · Comfy-Org/Krea-2 | models/vae | 0.3 GB | Download → |
| Total download · keep about the same free on disk | 18.0 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 24.0 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 8.0 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 Krea 2 file on 12.7 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 26.3 GB | 28.9 GB | 16.2 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · vantagewithai | 13.7 GB | 16.3 GB | 3.6 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · vantagewithai | 10.6 GB | 13.2 GB | spills 0.5 GB | very close to the original | Hugging Face → |
| Q5_K_M ← GGUF · vantagewithai | 8.9 GB | 11.5 GB | fits · 1.2 GB spare | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · vantagewithai | 7.5 GB | 10.1 GB | fits · 2.6 GB spare | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · vantagewithai | 6.0 GB | 8.6 GB | fits · 4.1 GB spare | noticeable loss of detail | Hugging Face → |
| Q2_K GGUF · vantagewithai | 4.9 GB | 7.5 GB | fits · 5.2 GB spare | heavy loss; a last resort | Hugging Face → |
“Needed” adds 1.8 GB of working memory for Krea 2 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 Krea 2 on a Mac 16 GB, send your time per image and peak VRAM and it will appear here, credited.
04With more VRAM
With 20 GB you could run Krea 2 at 8-bit or better (Q8_0, 13.7 GB) with no offloading.
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 Krea 2 need?
Around 7.5 GB with the smallest file (Q2_K) and 15.7 GB with an 8-bit file (FP8). The full 16-bit file needs about 28.9 GB.
Which Krea 2 file should I download for the Mac 16 GB?
Q5_K_M (8.9 GB) from vantagewithai/Krea-2-Turbo-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
FP8 or Q8_0 for Krea 2 on the Mac 16 GB?
Q8_0 (13.7 GB). The Mac 16 GB has no FP8 maths, so FP8 (13.1 GB) only saves memory and is a step further from the original.
How much do I need to download for Krea 2 on the Mac 16 GB?
18.0 GB: krea2_turbo-Q5_K_M.gguf, qwen3vl_4b_bf16.safetensors, qwen_image_vae.safetensors.