Model reference · open weights
FastWan-QAD is an open-weight video model from FastVideo, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
FastWan-QAD-FP8-1.3B Introduction FastWan-QAD-FP8-1.3B is the backward-compatible variant of the FastWan-QAD series, designed for RTX 4090 and other Ampere/Ada GPUs. It uses FP8 quantized linear layers paired with SageAttention2++, generating a 5-second 480p video in approximately 3.4 seconds — still well ahead of prior distilled methods. The model is built on Wan-AI/Wan2.1-T2V-1.3B-Diffusers and trained with quantization-aware distillation (QAD) for 3-step inference. For RTX 5090 users, see FastWan-QAD-1.3B for maximum speed with NVFP4. Model Overview - 3-step inference via quantization-aware distillation - FP8 linear layers compatible with Ampere, Ada, and Hopper GPUs - SageAttention2++ backend for attention computation - Trained at 480p (832×480) resolution, 81 frames (5 seconds at 16 fps) - No classifier-free guidance at inference time - Fast decoding via TAEHV tiny autoencoder Performance Inference Training More details coming soon. It would be greatly appreciated if you cite our paper:
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | FastVideo |
|---|---|
| Type | Video models |
| Parameters (lead) | 1.4B |
| Variants | 1 |
| Runs with | diffusers |
| Released | 2026-06-16 |
| Popularity | 310 downloads / month |
| Likes | 10 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| FastWan-QAD-FP8-1.3B | 1.4B | FP8 | ~1.6 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys fastwan-qad for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (fastwan-qad below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/videos/generations \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"fastwan-qad","prompt":"a drone shot over a forest"}'
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗
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