Check my GPU →

Can the Mac 64 GB run LTX-Video 13B (0.9.8)?

Yes. 16-bit fits on the Mac 64 GB with 22.8 GB to spare.

Video model · 13B64 GB unified · ~55.7 GB for the GPU · 273–800 GB/s · Apple SiliconData 2026-10-01
Runs well
Yes, with room to spare.

16-bit (28.6 GB) needs about 32.9 GB in use, so 22.8 GB of the 55.7 GB stays free: room for a larger image, a LoRA or a ControlNet.

Best file16-bit
File size28.6 GB
GPU memory needed~32.9 GB
Shared memory40 / 64 GB
Memory map · Mac 64 GB32.9 GB / 55.7 GB
028 GB56 GB
Weights 16-bit · 28.6 GBWorking memory · 3.5 GBReserve · 0.8 GBFree · 22.8 GB

01What to download

PartFileFolderSize
Modelltxv-13b-0.9.8-dev.safetensors
16-bit · Lightricks/LTX-Video
models/diffusion_models28.6 GBDownload →
Text encodert5-v1_1-xxl-encoder-Q8_0.gguf
T5-XXL GGUF Q8_0 · city96/t5-v1_1-xxl-encoder-gguf
models/text_encoders5.1 GBDownload →
Total download · keep about the same free on disk33.6 GB

Alternatives: T5-XXL FP16 (9.8 GB). On a Mac, FP8 text encoders do not load, so a 16-bit one is listed - or a GGUF one, loaded with “CLIPLoader (GGUF)” from the ComfyUI-GGUF nodes. Sizes from Hugging Face, 2026-10-01.

Shared memory: about 39.6 GB of your 64 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 LTX-Video 13B file on 55.7 GB

FileSizeNeededOn this cardQualityDownload
16-bit ←
SAFETENSORS · Lightricks
28.6 GB32.9 GBfits · 22.8 GB sparethe original weightsHugging Face →
Q8_0
GGUF · QuantStack
14.0 GB18.3 GBfits · 37.4 GB sparepractically identical to the originalHugging Face →
Q6_K
GGUF · QuantStack
10.9 GB15.2 GBfits · 40.5 GB sparevery close to the originalHugging Face →
Q5_K_M
GGUF · QuantStack
9.8 GB14.1 GBfits · 41.6 GB spareclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · QuantStack
8.8 GB13.1 GBfits · 42.6 GB sparegood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · QuantStack
6.5 GB10.8 GBfits · 44.9 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · QuantStack
4.7 GB9.0 GBfits · 46.7 GB spareheavy loss; a last resortHugging Face →

“Needed” adds 3.5 GB of working memory for LTX-Video 13B 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 LTX-Video 13B on a Mac 64 GB, send your time per image and peak VRAM and it will appear here, credited.

04About the Mac 64 GB

A Mac with 64 GB shares that memory between the CPU and the GPU. On current macOS the GPU may use about 55.7 GB of it by default (older macOS versions: about 51.5 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 64 GB: M1 Max, M1 Ultra, M2 Max, M2 Ultra, M3 Max, M4 Pro, M4 Max, M5 Pro, M5 Max (memory bandwidth 273–800 GB/s - the higher, the faster). Everything about Macs and local AI →

64 GB unified · ~55.7 GB for the GPU · 273–800 GB/s · Apple Silicon. Everything that runs on it →

05Questions

How much VRAM does LTX-Video 13B need?

Around 9.0 GB with the smallest file (Q2_K) and 20.0 GB with an 8-bit file (FP8). The full 16-bit file needs about 32.9 GB.

Which LTX-Video 13B file should I download for the Mac 64 GB?

16-bit (28.6 GB) from Lightricks/LTX-Video.

FP8 or Q8_0 for LTX-Video 13B on the Mac 64 GB?

Q8_0 (14.0 GB). The Mac 64 GB has no FP8 maths, so FP8 (15.7 GB) only saves memory and is a step further from the original.

How much do I need to download for LTX-Video 13B on the Mac 64 GB?

33.6 GB: ltxv-13b-0.9.8-dev.safetensors, t5-v1_1-xxl-encoder-Q8_0.gguf.