Wan 2.1 T2V 1.3B on Intel Celeron J1800 / N3710 / 3865U NAS (16 GB)

Can the Intel Celeron J1800 / N3710 / 3865U NAS (16 GB) run Wan 2.1 T2V 1.3B?

Barely: it runs very slowly (encoder unloaded after use)

Very slow (encoder unloaded after use). At FP16 it needs about 8.4 GB of 12.0 GB usable and takes about 47.9 h per clip.

Best precision: FP16
Memory mode: Text encoder offloaded
Time per clip: 47.9 h
Output: 832×480, 81 frames, 50 steps

Download Wan 2.1 T2V 1.3B

Original weights · Hugging Face

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

huggingface.co/Wan-AI/Wan2.1-T2V-1.3B (opens in a new tab)

No sign-in needed.

Official repo · GitHub

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

github.com/Wan-Video/Wan2.1 (opens in a new tab)

git clone https://github.com/Wan-Video/Wan2.1

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

How it’s rated

Quality 55Good quality (B) · 55 of 100: how capable the model is at FP16, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking.: How capable the model itself is at FP16, 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 Very slowencoder unloaded after use: How well it runs on the Intel Celeron J1800 / N3710 / 3865U NAS (16 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.	24.8 / 45
Memory fitFull marks when the model fits in the share of the NAS’s memory that models can use (the rest stays with the NAS system and its storage services); fewer when it goes past that limit.	20.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	0.5 / 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
Match score	60.2 / 100

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

Every precision on the Intel Celeron J1800 / N3710 / 3865U NAS (16 GB)

Quant	Memory needed	Available	Speed	Memory mode	Runs	Quality	Download
`FP16`	8.4 GB	12.0 GB	47.9 h	Text encoder offloaded	Very slowencoder unloaded after use	55Good quality (B) · 55 of 100: how capable the model is at FP16, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)
`FP8`	7.1 GB	12.0 GB	43.1 h	Text encoder offloaded	Very slowencoder unloaded after use	53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 58/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)

Other hardware that runs it

53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. AMD Radeon RX 9070 XT FP8 · 4.8 min · Runs well
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 5080 FP8 · 4.8 min · Runs well
53Fair quality (C) · 53 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 4080 SUPER FP8 · 5.1 min · Runs well
53Fair quality (C) · 53 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 · 3.6 min · Runs great
53Fair quality (C) · 53 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 4070 Ti SUPER FP8 · 5.8 min · Runs well
53Fair quality (C) · 53 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 5070 Ti FP8 · 5.8 min · Runs well

Quick answers

How much memory does Wan 2.1 T2V 1.3B need on the Intel Celeron J1800 / N3710 / 3865U NAS 16GB?

At FP16 it needs about 8.4 GB. The Intel Celeron J1800 / N3710 / 3865U NAS 16GB has 12.0 GB usable.

How long does Wan 2.1 T2V 1.3B take on the Intel Celeron J1800 / N3710 / 3865U NAS 16GB?

About 47.9 h per clip at FP16 and default settings, an estimate scaled from a reference timing by this hardware’s compute 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.