diff --git a/vllm_omni/engine/async_omni_engine.py b/vllm_omni/engine/async_omni_engine.py
index 15167105135..2813cac47e0 100644
--- a/vllm_omni/engine/async_omni_engine.py
+++ b/vllm_omni/engine/async_omni_engine.py
@@ -1598,6 +1598,7 @@ def _resolve_stage_configs(self, model: str, kwargs: dict[str, Any]) -> tuple[st
         stage_overrides_json = kwargs.pop("stage_overrides", None)
         kwargs.pop("_cli_explicit_keys", None)
         explicit_stage_configs = kwargs.pop("stage_configs", None)
+
         if explicit_stage_configs is not None:
             logger.warning(
                 "`stage_configs` is not part of the public API. "
@@ -1631,7 +1632,8 @@ def _resolve_stage_configs(self, model: str, kwargs: dict[str, Any]) -> tuple[st
             stage_overrides=stage_overrides,
         )
 
-        # Inject diffusion LoRA-related knobs from kwargs if not present in the stage config.
+        # Inject diffusion knobs (parallel_config, LoRA, quantization) from kwargs
+        # into resolved diffusion stages when not already set by YAML/model config.
         for cfg in stage_configs:
             try:
                 if not hasattr(cfg, "engine_args") or cfg.engine_args is None:
@@ -1644,6 +1646,42 @@ def _resolve_stage_configs(self, model: str, kwargs: dict[str, Any]) -> tuple[st
                     continue
                 if not hasattr(cfg, "engine_args") or cfg.engine_args is None:
                     cfg.engine_args = OmegaConf.create({})
+
+                if kwargs.get("parallel_config") is None:
+                    parallel_cli_fields = {
+                        "ulysses_degree": 1,
+                        "ring_degree": 1,
+                        "ulysses_mode": "strict",
+                        "sequence_parallel_size": None,
+                        "tensor_parallel_size": 1,
+                        "enable_expert_parallel": False,
+                        "cfg_parallel_size": 1,
+                        "vae_patch_parallel_size": 1,
+                        "use_hsdp": False,
+                        "hsdp_shard_size": -1,
+                        "hsdp_replicate_size": 1,
+                    }
+                    if not hasattr(cfg.engine_args, "parallel_config") or cfg.engine_args.parallel_config is None:
+                        values = {k: kwargs.get(k, d) for k, d in parallel_cli_fields.items()}
+                        if values["sequence_parallel_size"] is None:
+                            values["sequence_parallel_size"] = values["ulysses_degree"] * values["ring_degree"]
+                        cfg.engine_args.parallel_config = DiffusionParallelConfig(
+                            pipeline_parallel_size=1,
+                            data_parallel_size=1,
+                            **values,
+                        )
+                    else:
+                        # YAML/model config already set parallel_config; only override
+                        # fields that the user explicitly passed via kwargs.
+                        pc = cfg.engine_args.parallel_config
+                        for key in parallel_cli_fields:
+                            if key in kwargs:
+                                setattr(pc, key, kwargs[key])
+                        if "sequence_parallel_size" not in kwargs and (
+                            "ulysses_degree" in kwargs or "ring_degree" in kwargs
+                        ):
+                            pc.sequence_parallel_size = pc.ulysses_degree * pc.ring_degree
+
                 if kwargs.get("lora_path") is not None:
                     if not hasattr(cfg.engine_args, "lora_path") or cfg.engine_args.lora_path is None:
                         cfg.engine_args.lora_path = kwargs["lora_path"]
@@ -1708,7 +1746,7 @@ def _resolve_stage_configs(self, model: str, kwargs: dict[str, Any]) -> tuple[st
                     ):
                         cfg.engine_args.kv_cache_skip_layers = kv_cache_skip_layers
             except Exception as e:
-                logger.warning("Failed to inject LoRA config for stage: %s", e)
+                logger.warning("Failed to inject diffusion engine_args for stage: %s", e)
 
         return config_path, stage_configs