[diffusion] model: support a new model (#24994)
This commit is contained in:
@@ -39,6 +39,8 @@ default parameters when initializing and generating videos.
|
||||
| Helios Distilled | `BestWishYsh/Helios-Distilled` | 720p | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
|
||||
| LTX-2 (one/two-stage/TI2V) | `Lightricks/LTX-2` | 768×512<br>1536×1024 | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
|
||||
| LTX-2.3 (one/two-stage/TI2V/HQ) | `Lightricks/LTX-2.3` | 768×512<br>1536×1024<br>1920×1088 (HQ default) | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
|
||||
| Cosmos3-Nano (T2V / I2V / T2I) | `nvidia/Cosmos3-Nano` | 720p · 480p<br>1024×1024 (T2I) | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
|
||||
| Cosmos3-Super (T2V / I2V / T2I) | `nvidia/Cosmos3-Super` | 720p · 480p<br>1024×1024 (T2I) | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
|
||||
|
||||
**Note**:
|
||||
|
||||
@@ -56,6 +58,11 @@ default parameters when initializing and generating videos.
|
||||
- `resident` usually provides the best latency/throughput but uses much more VRAM.
|
||||
- `original` keeps official two-stage semantics without the premerged stage-2 transformer path.
|
||||
- Example (one prior run): `original` `154.67s`, `snapshot` `114.05s`, `resident` `75.71s`; peak VRAM trend is `original < snapshot < resident`.
|
||||
5. Cosmos3 ships in two sizes — `nvidia/Cosmos3-Nano` (8B) and
|
||||
`nvidia/Cosmos3-Super` (32B). Both share the same pipeline; the only
|
||||
difference is transformer depth and width, picked up from
|
||||
`transformer/config.json` at load time. A single checkpoint serves T2V,
|
||||
I2V (`--image-path`), and T2I (`--num-frames 1`).
|
||||
|
||||
### Image Generation Models
|
||||
|
||||
|
||||
@@ -4,7 +4,7 @@ SGLang Diffusion is a high-performance inference framework for image and video g
|
||||
|
||||
## Key Features
|
||||
|
||||
- Broad model support across Wan, Hunyuan, Qwen-Image, FLUX, Z-Image, GLM-Image, and more
|
||||
- Broad model support across Wan, Hunyuan, Cosmos3, Qwen-Image, FLUX, Z-Image, GLM-Image, and more
|
||||
- Fast inference with `sgl-kernel`, JIT kernels, scheduler improvements, and caching acceleration
|
||||
- Multiple interfaces: `sglang generate`, `sglang serve`, and an OpenAI-compatible API
|
||||
- Multi-platform support for NVIDIA, AMD, Intel XPU, Ascend, Apple Silicon, and Moore Threads
|
||||
|
||||
Reference in New Issue
Block a user