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e6066e8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 | ## Hunyuan1.5 Benchmark
### Executive Summary
This report presents a comprehensive performance evaluation of the **[Athena](https://github.com/world-sim-dev/athena)** framework compared to the baseline **[LightX2V](https://github.com/ModelTC/LightX2V)** framework. The benchmarks were conducted using the **[Hunyuan-1.5](https://github.com/Tencent-Hunyuan/HunyuanVideo-1.5)** model on NVIDIA H100 hardware.
---
### π―Test Environment & Versioning
#### Hardware & Settings
| Parameter | Value |
| ------------------- | -------------- |
| Hardware | NVIDIA H100 |
| Model | Hunyuan-1.5 480p_t2v_distilled |
| Precision | torch.bfloat16 |
| Inference Steps | 20 |
| Resolution | 480p |
| FPS | 24 |
| CFG | Disable |
#### Software Versioning
To ensure reproducibility, the following specific commits were used for this benchmark:
| Framework | Branch / Tag | Commit |
| --------- | ------------ | ------ |
| Athena | main|[5e6086b](https://github.com/world-sim-dev/athena/commit/5e6086b4dc2ab60bc4d44dbe39745b4354075121) |
| LightX2V | main | [5573905](https://github.com/ModelTC/LightX2V/commit/5573905f3f38d876d468b815f86d417a608975b6) |
### π Performance Benchmarks
π We compared the iteration speed (seconds per iteration) between Athena and LightX2V across three distinct Context Parallel (CP) configurations.
| Configuration | Frames | LightX2V (s/it) | Athena (s/it) | Speedup |
| ------------- | ------ | -------------- | -------------- | ------- |
| CP1 | 121 | 2.42 | **2.06** | **1.17x** π|
| CP2 | 121 | 1.38 | **1.13** | **1.22x** π|
| CP4 | 241 | 2.25 | **1.85** | **1.22x** π|
| CP8 | 241 | 1.28 | **1.01** | **1.27x** π|
---
### πΉ Output Comparison
| Framework | Video Result |
| --------- | ---------------------------- |
| Athena | <img src="../../../assets/athena_hunyuan_1_5_test_videos_20260213_155842_idx0_A_close-up815965.gif" width="480" /> |
| LightX2V | <img src="../../../assets/lightx2v_hunyuan_1_5_result_A_close-up122526.gif" width="480" /> |
### π‘ Reproduction Guide
To reproduce the results presented in this report, follow the steps below using the specified commit hashes.
#### Setup
```bash
git clone https://github.com/world-sim-dev/athena
cd athena
git checkout 5e6086b
pip install -r requirements.txt
pip install -r requirements-nodeps.txt
pip install -e ./pkgs/MagiCompiler --no-build-isolation --config-settings editable_mode=compat
# Clone and install LightX2V (for baseline comparison)
git clone https://github.com/ModelTC/LightX2V
cd lightx2v
git checkout 5573905
pip install -v .
```
#### Running Benchmarks
For Athena, run:
```
RESOLUTION=480p CFG_DISTILLED=true TASK=t2v CHECKPOINT_PATH=path/to/480p_t2v_distilled bash ./scripts/run_hunyuan.sh
```
For LightX2V:
Clone the scripts from [Benchmark for LightX2V](https://gist.github.com/wtr0504/d80bbebb7da1ef7b58f3e6faf1c68880) and run:
```
git clone https://gist.github.com/wtr0504/d80bbebb7da1ef7b58f3e6faf1c68880
MODEL_PATH=path/to/HunyuanVideo-1.5 DISTILL_CKPT=path/to/480p_t2v_distilled/diffusion_pytorch_model.safetensors bash run_hunyuan.sh
```
### π MagiCompiler Optimization Methodology
**Whole Graph Compilation**
Constant Folding & Dead Code Elimination: Streamlining the computation graph prior to execution.
**Coarse-grained Kernel Fusion**
MagiCompiler aggregates multiple smaller operators into larger, fused kernels. This optimization is critical for efficient execution on the GPU.
|