Compatibility Matrix¶

This page summarizes common model + optimization combinations.

For the canonical, code-level list of model IDs recognized by VideoGenerator.from_pretrained(...), see the registrations in fastvideo/registry.py (register_configs(...) entries).

Registered Model IDs¶

Every Hugging Face model ID registered in fastvideo/registry.py on main (commit 8d89f30d), grouped by family. Any ID below can be passed to VideoGenerator.from_pretrained(...); FastVideo resolves the matching pipeline and sampling defaults. The Family column is a documentation grouping: it follows each registration's declared model_family, except black-forest-labs/FLUX.1-dev, which declares none and is listed under flux for readability. The Workloads column shows each registration's declared workload_types; — means the entry is registered without a UI workload option but is still loadable by ID. The Example column links a runnable script in examples/inference/basic/ where one exists.

Note (stable_audio): the Stable Audio Open pipelines generate audio (StableAudioT2AConfig / StableAudioOpenSmallConfig); they are registered under the generic T2V workload option in the registry.

Note (Wan-VACE): not currently supported — no VACE pipeline or registered model ID exists on main (#1435). The closest supported path is the Wan2.1-Fun control pipeline (IRMChen/Wan2.1-Fun-1.3B-Control-Diffusers).

The symbols used have the following meanings:

• ✅ = Full compatibility
• ❌ = No compatibility
• ⭕ = Does not apply to this model

Models x Optimization¶

The HuggingFace Model ID can be passed directly to from_pretrained(). FastVideo then uses model-specific default settings for pipeline initialization and sampling.

Registered models absent from this table have not been validated against these optimizations: absence means untested, not incompatible.

Note: Wan2.2 TI2V 5B has some quality issues when performing I2V generation. We are working on fixing this issue.

***Lucy Edit Dev uses a non-commercial model license. FastVideo support is focused on inference integration for video editing workflows.

Sliding Tile Attn (Legacy Branch) entries refer to the archived sta_do_not_delete branch workflow, not active main inference wiring.

Canonical Supported IDs¶

The authoritative source for model-ID recognition is fastvideo/registry.py. If a model ID is registered there, FastVideo can resolve default pipeline and sampling configuration for it.

Note (GEN3C): The official nvidia/GEN3C-Cosmos-7B repo provides a raw model.pt checkpoint. Use a Diffusers-format repo (for example, FastVideo/GEN3C-Cosmos-7B-Diffusers) or convert locally with scripts/checkpoint_conversion/convert_gen3c_to_fastvideo.py.

Hardware and OS¶

Per the installation guides:

• NVIDIA GPU (x86_64) — CUDA 12.6 or 13.0; see the GPU install guide.
• NVIDIA DGX Spark (GB10, aarch64) — CUDA 13, from-source kernel build; see the DGX Spark install guide.
• Apple silicon (MPS) — macOS 14 or newer; see the MPS install guide and basic_mps.py.

Optimization-specific hardware constraints (e.g. STA requiring Hopper) are listed under Special requirements.

Special requirements¶

Sliding Tile Attention¶

• Full STA pipeline usage is on the archived branch: https://github.com/hao-ai-lab/FastVideo/tree/sta_do_not_delete
• STA currently requires Hopper GPUs (H100s).

TurboWan2.1 (TurboDiffusion)¶

• Uses TurboDiffusionPipeline with RCM scheduler for 1-4 step generation
• Requires SLA attention backend: export FASTVIDEO_ATTENTION_BACKEND=SLA_ATTN
• Uses guidance_scale=1.0 (no classifier-free guidance)

Matrix Game 2.0¶

• Image-to-video game world models with keyboard/mouse control input
• Three variants available: Base (universal), GTA, and TempleRun
• Each variant has different keyboard dimensions for control inputs