SkyReels V2 Diffusion Forcing 1.3B on Arduino UNO Q (4 GB)

Can the Arduino UNO Q (4 GB) run SkyReels V2 Diffusion Forcing 1.3B?

No, it doesn’t fit

No. SkyReels V2 Diffusion Forcing 1.3B needs about 9.8 GB even at FP8; the Arduino UNO Q (4 GB) has 2.8 GB usable.

Download SkyReels V2 Diffusion Forcing 1.3B

Original weights · Hugging Face

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

huggingface.co/Skywork/SkyReels-V2-DF-1.3B-540P (opens in a new tab)

No sign-in needed.

Official repo · GitHub

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

github.com/SkyworkAI/SkyReels-V2 (opens in a new tab)

git clone https://github.com/SkyworkAI/SkyReels-V2

Links checked 2 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 50Fair quality (C) · 50 of 100: how capable the model is at FP8, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking.: How capable the model itself is at FP8, from its editorial quality tier scaled by the quantization or precision. It’s the same on any hardware that runs this variant. Scale: A+ 85+ · A 70+ · B 55+ · C 40+ · D under 40.
Runs Won't run: How well it runs on the Arduino UNO Q (4 GB): speed, capped by how well it fits in memory. Runs great: 30+ tokens/s (or near the image, video or decision speed target) · Runs well: 10+ tokens/s · Slow: 3+ tokens/s · Very slow: under 3 · Won’t run: doesn’t fit even with offload. A tight fit or RAM offload caps it at Runs well; heavy offload caps it at Slow.

Match score

To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.	6.9 / 45
Memory fitFull marks when the model fits in the share of unified memory the GPU can use; fewer when it goes past that limit.	0.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	0.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	0.0 / 15
Match score	6.9 / 100

The match score orders results; it is not shown as a grade. Quality and Runs are the two ratings in the tables.

It doesn’t fit, so only a reduced share of the quality points counts and fit, speed and memory use score zero.

Every precision on the Arduino UNO Q (4 GB)

Quant	Memory needed	Available	Speed	Memory mode	Runs	Quality	Download
`FP16`	10.3 GB	2.8 GB	—	—	Won't run	52Fair quality (C) · 52 of 100: how capable the model is at FP16, whatever it runs on. Match score 7/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)
`FP8`	9.8 GB	2.8 GB	—	—	Won't run	50Fair quality (C) · 50 of 100: how capable the model is at FP8, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)

Hardware that can run it

50Fair quality (C) · 50 of 100: how capable the model is at FP8, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4090 FP8 · 4.5 min · Runs well
50Fair quality (C) · 50 of 100: how capable the model is at FP8, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. AMD Radeon RX 7900 XTX FP8 · 5.0 min · Runs well
50Fair quality (C) · 50 of 100: how capable the model is at FP8, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 5090 FP8 · 3.8 min · Runs great
50Fair quality (C) · 50 of 100: how capable the model is at FP8, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 3090 FP8 · 8.5 min · Runs well
50Fair quality (C) · 50 of 100: how capable the model is at FP8, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. AMD Radeon RX 9070 XT FP8 · 6.3 min · Runs well (encoder in RAM)
50Fair quality (C) · 50 of 100: how capable the model is at FP8, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 5080 FP8 · 6.3 min · Runs well (encoder in RAM)

Models that do run on the Arduino UNO Q (4 GB)

35Basic quality (D) · 35 of 100: how capable the model is at FP16, whatever it runs on. Match score 42/100 (quality, fit, speed and memory use) sets the ranking. AnimateDiff v3 (SD 1.5) FP16 · 2.5 h

Quick answers

How much memory does SkyReels V2 Diffusion Forcing 1.3B need on the Arduino UNO Q 4GB?

Even at FP8 it needs about 9.8 GB; the Arduino UNO Q 4GB has 2.8 GB usable.

What can the Arduino UNO Q 4GB run instead?

AnimateDiff v3 (SD 1.5) runs best on it; the page lists more, each with its speed.

What hardware can run SkyReels V2 Diffusion Forcing 1.3B?

RTX 4090 24GB, RX 7900 XTX 24GB and RTX 5090 32GB run it; the page lists more, each with its speed.

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.