LTX-Video 13B 0.9.8 (distilled) on AMD Radeon AI PRO R9700

Can the AMD Radeon AI PRO R9700 run LTX-Video 13B 0.9.8 (distilled)?

82 pts

Yes, with little memory to spare

Tight fit. At FP8 it needs about 30.1 GB of 32.0 GB usable, with an estimated speed of 73 s.

Best precision: FP8
Memory mode: Everything on GPU
Time per clip: 73 s
Output: 1216×704, 121 frames, 8 steps

Download LTX-Video 13B 0.9.8 (distilled)

Original weights · Hugging Face

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

huggingface.co/Lightricks/LTX-Video-0.9.8-13B-distilled (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-Video (opens in a new tab)

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

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

How the A 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.	30.0 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	23.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	15.0 / 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	83.0 / 100	82 ptsGreat (A) · 82 of 100 points: Model quality 30.0/45, Memory fit 23.0/25, Speed 15.0/15, 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 AMD Radeon AI PRO R9700

Precision	Memory needed	Available	Time per output	Memory mode	Fit	Grade · points	Download
`FP16`	20.6 GB	32.0 GB	1.7 min	Sequential CPU offload	Runs well	72 ptsGreat (A) · 72 of 100 points: Model quality 30.6/45, Memory fit 12.0/25, Speed 15.0/15, Memory use 14.9/15	Original weights (opens in a new tab)
`FP8`	30.1 GB	32.0 GB	73 s	Everything on GPU	Tight fit	82 ptsGreat (A) · 82 of 100 points: Model quality 30.0/45, Memory fit 23.0/25, Speed 15.0/15, Memory use 15.0/15	Original weights (opens in a new tab)

Other hardware that runs it

82 ptsGreat (A) · 82 of 100 points: Model quality 30.0/45, Memory fit 23.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090 FP8 · 45 s
82 ptsGreat (A) · 82 of 100 points: Model quality 30.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.5/15 AMD Ryzen AI Max+ 395 (128 GB) FP16 · 1.9 min
82 ptsGreat (A) · 82 of 100 points: Model quality 30.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.5/15 NVIDIA RTX PRO 6000 Blackwell FP16 · 44 s
80 ptsGreat (A) · 80 of 100 points: Model quality 30.0/45, Memory fit 25.0/25, Speed 11.3/15, Memory use 14.5/15 Apple M4 Max (64 GB) FP8 · 5.3 min
80 ptsGreat (A) · 80 of 100 points: Model quality 30.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.6/15 NVIDIA GB10 (128 GB) FP16 · 2.1 min
78 ptsGreat (A) · 78 of 100 points: Model quality 30.0/45, Memory fit 25.0/25, Speed 8.7/15, Memory use 15.0/15 Apple M4 Pro (48 GB) FP8 · 8.9 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.