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26 changes: 26 additions & 0 deletions README.md
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[![Unit Tests](https://github.com/AI-Hypercomputer/maxdiffusion/actions/workflows/UnitTests.yml/badge.svg)](https://github.com/AI-Hypercomputer/maxdiffusion/actions/workflows/UnitTests.yml)

# What's new?
- **`2026/03/31`**: Wan2.2 SenCache inference is now supported for T2V and I2V (up to 1.4x speedup)
- **`2026/03/25`**: Wan2.1 and Wan2.2 Magcache inference is now supported
- **`2026/03/25`**: LTX-2 Video Inference is now supported
- **`2026/01/29`**: Wan LoRA for inference is now supported
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* For Wan2.2 T2V, use `base_wan_27b.yml`.
* For Wan2.2 I2V, use `base_wan_i2v_27b.yml`.

### Caching Mechanisms

Wan 2.x pipelines support several caching strategies to accelerate inference by skipping redundant transformer forward passes. These are **mutually exclusive** — enable only one at a time.

| Cache Type | Config Flag | Supported Pipelines | Speedup | Description |
| --- | --- | --- | --- | --- |
| **CFG Cache** | `use_cfg_cache: True` | Wan 2.1 T2V, Wan 2.2 T2V/I2V | ~1.2x | FasterCache-style: caches the unconditional branch and applies FFT frequency-domain compensation on skipped steps. |
| **SenCache** | `use_sen_cache: True` | Wan 2.2 T2V/I2V | ~1.4x | Sensitivity-Aware Caching ([arXiv:2602.24208](https://arxiv.org/abs/2602.24208)): predicts output change via first-order sensitivity S = α_x·‖Δx‖ + α_t·\|Δt\|. Skips the full CFG forward pass when predicted change is below tolerance ε. |

To enable a caching mechanism, set the corresponding flag in your config YAML or pass it as a command-line override:

```bash
# Example: enable SenCache for Wan 2.2 T2V
python src/maxdiffusion/generate_wan.py \
src/maxdiffusion/configs/base_wan_27b.yml \
use_sen_cache=True \
...

# Example: enable CFG Cache for Wan 2.2 I2V
python src/maxdiffusion/generate_wan.py \
src/maxdiffusion/configs/base_wan_i2v_27b.yml \
use_cfg_cache=True \
...
```

## Flux

First make sure you have permissions to access the Flux repos in Huggingface.
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