diff --git a/examples/offline_inference/glm_image/end2end.py b/examples/offline_inference/glm_image/end2end.py
index 3cb74f82cca..13bcd23f55a 100644
--- a/examples/offline_inference/glm_image/end2end.py
+++ b/examples/offline_inference/glm_image/end2end.py
@@ -238,8 +238,24 @@ def main(args: argparse.Namespace) -> None:
     if args.negative_prompt:
         prompt_dict["negative_prompt"] = args.negative_prompt
 
+    # Build cache-dit config if requested
+    cache_config = None
+    if args.cache_backend == "cache_dit":
+        cache_config = {
+            "Fn_compute_blocks": 1,
+            "Bn_compute_blocks": 0,
+            "max_warmup_steps": 4,
+            "residual_diff_threshold": 0.24,
+            "max_continuous_cached_steps": 3,
+            "enable_taylorseer": False,
+            "taylorseer_order": 1,
+            "scm_steps_mask_policy": None,
+            "scm_steps_policy": "dynamic",
+        }
+
     # Initialize Omni with multistage config
     print("\nInitializing Omni with multistage pipeline...")
+    print(f"  Cache backend: {args.cache_backend or 'None (no acceleration)'}")
     start_time = time.time()
 
     omni = Omni(
@@ -247,6 +263,9 @@ def main(args: argparse.Namespace) -> None:
         stage_configs_path=config_path,
         log_stats=args.enable_stats,
         stage_init_timeout=args.stage_init_timeout,
+        cache_backend=args.cache_backend,
+        cache_config=cache_config,
+        enable_cache_dit_summary=getattr(args, "enable_cache_dit_summary", False),
         enable_diffusion_pipeline_profiler=args.enable_diffusion_pipeline_profiler,
     )
 
@@ -444,6 +463,20 @@ def parse_args() -> argparse.Namespace:
         help="Number of images to generate (default: 1)",
     )
 
+    # Cache acceleration
+    parser.add_argument(
+        "--cache-backend",
+        type=str,
+        default=None,
+        choices=["cache_dit"],
+        help="Cache backend for DiT acceleration. Default: None (no cache).",
+    )
+    parser.add_argument(
+        "--enable-cache-dit-summary",
+        action="store_true",
+        help="Enable cache-dit summary logging after diffusion forward passes.",
+    )
+
     # Runtime options
     parser.add_argument(
         "--enable-stats",
diff --git a/vllm_omni/diffusion/cache/cache_dit_backend.py b/vllm_omni/diffusion/cache/cache_dit_backend.py
index 831d55f9850..e5337be1276 100644
--- a/vllm_omni/diffusion/cache/cache_dit_backend.py
+++ b/vllm_omni/diffusion/cache/cache_dit_backend.py
@@ -61,6 +61,8 @@ def _build_db_cache_config(cache_config: Any) -> DBCacheConfig:
         max_cached_steps=cache_config.max_cached_steps,
         max_continuous_cached_steps=cache_config.max_continuous_cached_steps,
         residual_diff_threshold=cache_config.residual_diff_threshold,
+        force_refresh_step_hint=cache_config.force_refresh_step_hint,
+        force_refresh_step_policy=cache_config.force_refresh_step_policy,
     )
 
 
@@ -1091,6 +1093,36 @@ def refresh_cache_context(pipeline: Any, num_inference_steps: int, verbose: bool
     return refresh_cache_context
 
 
+def enable_cache_for_glm_image(pipeline: Any, cache_config: Any) -> Callable[[int], None]:
+    """Enable cache-dit for GLM-Image pipeline.
+
+    GLM-Image processes prompt and image by calling the transformer before the
+    denoising loop. When an input image is provided (editing mode), the cache must
+    be force-refreshed after the preprocessing step so stale hidden states are
+    discarded. Set force_refresh_step_hint = 1 for editing, None for text-to-image.
+    """
+    db_cache_config = _build_db_cache_config(cache_config)
+
+    calibrator_config = None
+    if cache_config.enable_taylorseer:
+        calibrator_config = TaylorSeerCalibratorConfig(taylorseer_order=cache_config.taylorseer_order)
+        logger.info(f"TaylorSeer enabled with order={cache_config.taylorseer_order}")
+
+    logger.info(
+        f"Enabling cache-dit on GLM-Image transformer: "
+        f"Fn={db_cache_config.Fn_compute_blocks}, "
+        f"Bn={db_cache_config.Bn_compute_blocks}, "
+        f"W={db_cache_config.max_warmup_steps}, "
+        f"force_refresh_step_hint={db_cache_config.force_refresh_step_hint}, "
+    )
+
+    cache_dit.enable_cache(
+        pipeline.transformer,
+        cache_config=db_cache_config,
+        calibrator_config=calibrator_config,
+    )
+
+
 def enable_cache_for_flux2(pipeline: Any, cache_config: Any) -> Callable[[int], None]:
     """Enable cache-dit for Flux.2-dev pipeline.
 
@@ -1180,6 +1212,7 @@ def refresh_cache_context(pipeline: Any, num_inference_steps: int, verbose: bool
         "LTX2Pipeline": enable_cache_for_ltx2,
         "LTX2ImageToVideoPipeline": enable_cache_for_ltx2,
         "BagelPipeline": enable_cache_for_bagel,
+        "GlmImagePipeline": enable_cache_for_glm_image,
         "Flux2Pipeline": enable_cache_for_flux2,
     }
 )
diff --git a/vllm_omni/diffusion/data.py b/vllm_omni/diffusion/data.py
index f15aae6a026..052149046da 100644
--- a/vllm_omni/diffusion/data.py
+++ b/vllm_omni/diffusion/data.py
@@ -264,6 +264,12 @@ class DiffusionCacheConfig:
     # Used by cache-dit for scm mask generation. If this value changes during inference,
     # we will re-generate the scm mask and refresh the cache context.
     num_inference_steps: int | None = None
+    # Force refresh the cache at a specific step index hint, useful for models like
+    # GLM-Image (image preprocessing step in editing mode).
+    force_refresh_step_hint: int | None = None
+    # Policy for force refresh: "once" refreshes only at the hint step,
+    # "repeat" refreshes every force_refresh_step_hint steps.
+    force_refresh_step_policy: str = "once"
 
     # Additional parameters that may be passed but not explicitly defined
     _extra_params: dict[str, Any] = field(default_factory=dict, repr=False)