[Model][Feat] Support Minimax-H3 quality grading requests through dynamic loading/unloading with Cache-DiT (#5853)

Signed-off-by: mglyn <1203789601@qq.com>
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Mu GuanLin authored and GitHub committed 2026-08-07 09:07:23 +00:00
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@@ -6,6 +6,7 @@
- [Overview](#overview)
- [Quick Start](#quick-start)
- [Example Script](#example-script)
- [Request-Scoped Quality](#request-scoped-quality-minimax-h3)
- [Acceleration Methods](#acceleration-methods)
- [Configuration Parameters](#configuration-parameters)
- [Best Practices](#best-practices)
@@ -140,6 +141,43 @@ vllm serve Qwen/Qwen-Image --omni --port 8091 \
--cache-config '{"Fn_compute_blocks": 1, "residual_diff_threshold": 0.12}'
```
## Request-Scoped Quality (MiniMax H3)
MiniMax H3 can switch Cache-DiT at the request boundary without enabling a
cache backend at server startup. Add a quality field to an online request:
```bash
# Native reference path for this request.
-F 'quality=lossless'
# H3's conservative Cache-DiT profile for this request.
-F 'quality=high'
```
For offline inference, set the same field on the sampling parameters:
```python
OmniDiffusionSamplingParams(
quality="high",
num_inference_steps=50,
extra_args={"task": "t2va", "duration": 5.0, "audio_flow_shift": 3.0},
)
```
| Server startup | Request quality | Behavior |
|---|---|---|
| `--cache-backend cache_dit` | omitted | Use or restore the startup Cache-DiT profile |
| `--cache-backend cache_dit` | `lossless` | Remove Cache-DiT hooks and run the reference path |
| `--cache-backend cache_dit` | `high` | Use or install H3's conservative Cache-DiT profile |
| no Cache-DiT | omitted or `lossless` | Run the reference path |
| no Cache-DiT | `high` | Install H3's conservative Cache-DiT profile |
The startup option is only needed when omitted-quality requests should use the
server-configured Cache-DiT profile by default.
See the [MiniMax H3 recipe](https://github.com/vllm-project/vllm-omni/blob/main/recipes/MiniMaxAI/MiniMax-H3.md#request-scoped-quality)
for a complete request and measured trade-off.
---
## Acceleration Methods