[Model] Add MiniMax H3 diffusion support (#5691)

docs/user_guide/diffusion/attention_backends.md

@@ -14,8 +14,8 @@ The full set of backends and their platform defaults is in the **Backend Options
 
 | Value | Notes |
 |---|---|
-| `TRTLLM_ATTN` | FlashInfer's trtllm-gen FMHA (TensorRT-LLM's generated kernels, vendored by FlashInfer). BF16, GQA native, `head_dim=128`. Datacenter Blackwell only (sm_100 / sm_103). Supports **Skip-Softmax** sparse attention and **SAGE** quantized attention — see below. Requires `flashinfer`. |
-| `FLASH_ATTN` | Wraps FlashAttention 2. Default on Hopper / Ada / Ampere when `flash-attn` is installed. |
+| `TRTLLM_ATTN` | FlashInfer's trtllm-gen FMHA (TensorRT-LLM's generated kernels, vendored by FlashInfer). BF16, GQA native, `head_dim=128`. Datacenter Blackwell only (sm_100 / sm_103). Supports **Skip-Softmax** sparse attention — see below. Requires `flashinfer`. |
+| `FLASH_ATTN` | Wraps FlashAttention 4 on Blackwell when `flash-attn-4` is installed, then falls back to FlashAttention 3/2. Default on Hopper / Ada / Ampere when a compatible FlashAttention package is installed. |
 | `CUDNN_ATTN` | Pins `sdpa_kernel([CUDNN_ATTENTION])`. Default on Blackwell (sm_10x / sm_12x) with cuDNN ≥ 9.5. Wins on mask-heavy DiTs (HunyuanVideo-1.5: 2× e2e vs SDPA). |
 | `FLASHINFER_ATTN` | Calls FlashInfer's dense `single_prefill_with_kv_cache` directly with `custom_mask` for non-causal masked attention. Used as Blackwell fallback when cuDNN is unavailable. Requires `flashinfer`. |
 | `TORCH_SDPA` | PyTorch `scaled_dot_product_attention` with the default backend dispatcher. Most conservative; always available. |
@@ -222,6 +222,30 @@ Same prompt and seed across runs. `Total generation time` from `text_to_video.py
 
 Pattern: mask-heavy DiTs (HV-1.5, Qwen-Image) favor `CUDNN_ATTN`; lighter-mask DiTs and TP-saturated configs (Wan 2.2, FLUX.2 TP=2) tie within noise.
 
+## Known Limitations
+
+### LTX-2.0: `CUDNN_ATTN` crashes under torch.compile
+
+LTX-2's audio attention has a symbolic head_dim under torch.compile tracing. cuDNN's SDPA backend selector rejects symbolic dims and Dynamo aborts compilation. Tracked in [#3121](https://github.com/vllm-project/vllm-omni/issues/3121).
+
+**Workaround**: explicitly select `FLASHINFER_ATTN` or `TORCH_SDPA` for LTX-2.0:
+
+```bash
+DIFFUSION_ATTENTION_BACKEND=FLASHINFER_ATTN python examples/offline_inference/text_to_video/text_to_video.py \
+    --model Lightricks/LTX-2 ...
+```
+
+### FlashAttention-4 on Blackwell
+
+Install the optional CUDA 13 extra to use the CuTe-based FA4 path:
+
+```bash
+pip install 'vllm-omni[fa4]'
+```
+
+`FLASH_ATTN` prefers `flash_attn.cute` on Blackwell and falls back to FA3/FA2
+when it is unavailable. Version `4.0.0b18` is required; earlier beta
+wheels had known JIT failures on Blackwell.
 
 ## Choosing a Backend Manually