Can the Mac 16 GB run LTX-2 (19B)?
Not entirely. Even Q2_K is 0.2 GB over 12.7 GB, so ComfyUI keeps part of it in system RAM.
Nothing fits entirely, but Q2_K (8.1 GB) overflows by only about 0.2 GB. ComfyUI keeps that part in system RAM automatically: slower than a full fit, but usable.
01With more VRAM
With 32 GB you could run LTX-2 at 8-bit or better (Q8_0, 20.4 GB) with no offloading: for example on the RTX 5090 32 GB.
02Every LTX-2 file on 12.7 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit GGUF · unsloth | 37.8 GB | 42.6 GB | 29.9 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · unsloth | 20.4 GB | 25.2 GB | 12.5 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · unsloth | 16.0 GB | 20.8 GB | 8.1 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · unsloth | 14.3 GB | 19.1 GB | 6.4 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · unsloth | 12.8 GB | 17.6 GB | 4.9 GB too big | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · unsloth | 10.1 GB | 14.9 GB | 2.2 GB too big | noticeable loss of detail | Hugging Face → |
| Q2_K ← GGUF · unsloth | 8.1 GB | 12.9 GB | spills 0.2 GB | heavy loss; a last resort | Hugging Face → |
“Needed” adds 4 GB of working memory for LTX-2 and a 0.8 GB reserve. Sizes 2026-10-01.
03What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | ltx-2-19b-dev-Q2_K.gguf Q2_K · unsloth/LTX-2-GGUF | models/unet | 8.1 GB | Download → |
| Text encoder | gemma_3_12B_it.safetensors Gemma 3 12B BF16 · Comfy-Org/ltx-2 | models/text_encoders | 24.4 GB | Download → |
| VAE | ltx-2-19b-dev_video_vae.safetensors LTX-2 video VAE · unsloth/LTX-2-GGUF | models/vae | 2.4 GB | Download → |
| Also needed | ltx-2-19b-dev_audio_vae.safetensors LTX-2 audio VAE · unsloth/LTX-2-GGUF | models/vae | 0.2 GB | Download → |
| Also needed | ltx-2-19b-dev_embeddings_connectors.safetensors LTX-2 text embeddings connectors (projection) · unsloth/LTX-2-GGUF | models/text_encoders | 2.9 GB | Download → |
| Total download · keep about the same free on disk | 38.0 GB | |||
Only for some workflows: LTX-2 spatial upscaler x2 (1.0 GB, official two-stage template). 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 44.0 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 28.0 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
04The text encoder
Take the smallest Gemma 3 12B file (9.4 GB): it is the only one that fits in 12.7 GB on its own. Sizes: 16-bit 24.4 GB, FP8 13.2 GB, FP4 mixed 9.4 GB. Why the encoder does not count against VRAM →
05Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run LTX-2 on a Mac 16 GB, send your time per image and peak VRAM and it will appear here, credited.
06About 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 →
07Questions
How much VRAM does LTX-2 need?
Around 12.9 GB with the smallest file (Q2_K) and 25.2 GB with an 8-bit file (Q8_0). The full 16-bit file needs about 42.6 GB.
Which LTX-2 file should I download for the Mac 16 GB?
Q2_K (8.1 GB) from unsloth/LTX-2-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
How much do I need to download for LTX-2 on the Mac 16 GB?
38.0 GB: ltx-2-19b-dev-Q2_K.gguf, gemma_3_12B_it.safetensors, ltx-2-19b-dev_video_vae.safetensors, ltx-2-19b-dev_audio_vae.safetensors, ltx-2-19b-dev_embeddings_connectors.safetensors.