LTX-2 (19B, video + audio) on Apple M2 Pro (32 GB)

Can the Apple M2 Pro (32 GB) run LTX-2 (19B, video + audio)?

63 pts

Yes, with little memory to spare

Tight fit. At Q8 GGUF it needs about 19.5 GB of 21.4 GB usable, with an estimated speed of 2.1 h.

Best precision: Q8 GGUF
Memory mode: Sequential CPU offload
Time per clip: 2.1 h
Output: 1280×704, 121 frames, 40 steps

Download LTX-2 (19B, video + audio)

Recommended for the Apple M2 Pro (32 GB): q8_gguf. Every other precision has its own download link in the table below.

Quantized files · GGUF for ComfyUI

Smaller GGUF versions for ComfyUI (with the ComfyUI-GGUF node). No sign-in needed; the model’s license still applies.

Download the q8_gguf (Q8_0) file (opens in a new tab)

huggingface.co/unsloth/LTX-2-GGUF (opens in a new tab)

Original weights · Hugging Face

Full-precision files from Lightricks, for fine-tuning, vLLM, Transformers, Diffusers or ComfyUI.

huggingface.co/Lightricks/LTX-2 (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Lightricks. The weights themselves download from Hugging Face.

github.com/Lightricks/LTX-2 (opens in a new tab)

git clone https://github.com/Lightricks/LTX-2

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

How the B grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.	36.5 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	10.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	2.3 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	15.0 / 15
Total	63.9 / 100	63 ptsGood (B) · 63 of 100 points: Model quality 36.5/45, Memory fit 10.0/25, Speed 2.3/15, Memory use 15.0/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every precision on the Apple M2 Pro (32 GB)

Precision	Memory needed	Available	Time per output	Memory mode	Fit	Grade · points	Download
`FP16`	25.6 GB	21.4 GB	—	—	Won't run	11 ptsWon't run (F) · 11 of 100 points: Model quality 11.1/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	Original weights (opens in a new tab)
`FP8`	19.0 GB	21.4 GB	1.6 h	Sequential CPU offload	Tight fit	63 ptsGood (B) · 63 of 100 points: Model quality 36.2/45, Memory fit 10.0/25, Speed 2.6/15, Memory use 15.0/15	Original weights (opens in a new tab)
`Q8 GGUF`	19.5 GB	21.4 GB	2.1 h	Sequential CPU offload	Tight fit	63 ptsGood (B) · 63 of 100 points: Model quality 36.5/45, Memory fit 10.0/25, Speed 2.3/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q4 GGUF`	16.4 GB	21.4 GB	2.1 h	Sequential CPU offload	Runs well	63 ptsGood (B) · 63 of 100 points: Model quality 34.3/45, Memory fit 12.0/25, Speed 2.3/15, Memory use 15.0/15	GGUF (opens in a new tab)

Other hardware that runs it

88 ptsExcellent (S) · 88 of 100 points: Model quality 36.9/45, Memory fit 25.0/25, Speed 11.8/15, Memory use 15.0/15 NVIDIA RTX PRO 6000 Blackwell FP16 · 4.9 min
84 ptsGreat (A) · 84 of 100 points: Model quality 36.9/45, Memory fit 25.0/25, Speed 7.3/15, Memory use 15.0/15 AMD Ryzen AI Max+ 395 (128 GB) FP16 · 12.8 min
83 ptsGreat (A) · 83 of 100 points: Model quality 36.9/45, Memory fit 25.0/25, Speed 7.0/15, Memory use 15.0/15 NVIDIA GB10 (128 GB) FP16 · 13.9 min
81 ptsGreat (A) · 81 of 100 points: Model quality 36.9/45, Memory fit 25.0/25, Speed 4.2/15, Memory use 15.0/15 Apple M4 Max (128 GB) FP16 · 39.1 min
79 ptsGreat (A) · 79 of 100 points: Model quality 34.3/45, Memory fit 20.0/25, Speed 9.8/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090 Q4 GGUF · 7.0 min
78 ptsGreat (A) · 78 of 100 points: Model quality 36.9/45, Memory fit 25.0/25, Speed 4.8/15, Memory use 12.1/15 Apple M2 Ultra (192 GB) FP16 · 29.1 min

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.