diff --git a/comfy/controlnet.py b/comfy/controlnet.py
index e3dfedf55..f08ff4b36 100644
--- a/comfy/controlnet.py
+++ b/comfy/controlnet.py
@@ -253,7 +253,10 @@ class ControlNet(ControlBase):
                 to_concat = []
                 for c in self.extra_concat_orig:
                     c = c.to(self.cond_hint.device)
-                    c = comfy.utils.common_upscale(c, self.cond_hint.shape[3], self.cond_hint.shape[2], self.upscale_algorithm, "center")
+                    c = comfy.utils.common_upscale(c, self.cond_hint.shape[-1], self.cond_hint.shape[-2], self.upscale_algorithm, "center")
+                    if c.ndim < self.cond_hint.ndim:
+                        c = c.unsqueeze(2)
+                        c = comfy.utils.repeat_to_batch_size(c, self.cond_hint.shape[2], dim=2)
                     to_concat.append(comfy.utils.repeat_to_batch_size(c, self.cond_hint.shape[0]))
                 self.cond_hint = torch.cat([self.cond_hint] + to_concat, dim=1)
 
@@ -585,11 +588,18 @@ def load_controlnet_flux_instantx(sd, model_options={}):
 
 def load_controlnet_qwen_instantx(sd, model_options={}):
     model_config, operations, load_device, unet_dtype, manual_cast_dtype, offload_device = controlnet_config(sd, model_options=model_options)
-    control_model = comfy.ldm.qwen_image.controlnet.QwenImageControlNetModel(operations=operations, device=offload_device, dtype=unet_dtype, **model_config.unet_config)
+    control_latent_channels = sd.get("controlnet_x_embedder.weight").shape[1]
+
+    extra_condition_channels = 0
+    concat_mask = False
+    if control_latent_channels == 68: #inpaint controlnet
+        extra_condition_channels = control_latent_channels - 64
+        concat_mask = True
+    control_model = comfy.ldm.qwen_image.controlnet.QwenImageControlNetModel(extra_condition_channels=extra_condition_channels, operations=operations, device=offload_device, dtype=unet_dtype, **model_config.unet_config)
     control_model = controlnet_load_state_dict(control_model, sd)
     latent_format = comfy.latent_formats.Wan21()
     extra_conds = []
-    control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, load_device=load_device, manual_cast_dtype=manual_cast_dtype, extra_conds=extra_conds)
+    control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, concat_mask=concat_mask, load_device=load_device, manual_cast_dtype=manual_cast_dtype, extra_conds=extra_conds)
     return control
 
 def convert_mistoline(sd):
diff --git a/comfy/text_encoders/llama.py b/comfy/text_encoders/llama.py
index 4c976058f..5e11956b5 100644
--- a/comfy/text_encoders/llama.py
+++ b/comfy/text_encoders/llama.py
@@ -128,11 +128,12 @@ def precompute_freqs_cis(head_dim, position_ids, theta, rope_dims=None, device=N
 
 
 def apply_rope(xq, xk, freqs_cis):
+    org_dtype = xq.dtype
     cos = freqs_cis[0]
     sin = freqs_cis[1]
     q_embed = (xq * cos) + (rotate_half(xq) * sin)
     k_embed = (xk * cos) + (rotate_half(xk) * sin)
-    return q_embed, k_embed
+    return q_embed.to(org_dtype), k_embed.to(org_dtype)
 
 
 class Attention(nn.Module):
diff --git a/comfy_extras/nodes_easycache.py b/comfy_extras/nodes_easycache.py
index 9d2988f5f..c170e9fd9 100644
--- a/comfy_extras/nodes_easycache.py
+++ b/comfy_extras/nodes_easycache.py
@@ -162,7 +162,12 @@ def easycache_sample_wrapper(executor, *args, **kwargs):
             logging.info(f"{easycache.name} [verbose] - output_change_rates {len(output_change_rates)}: {output_change_rates}")
             logging.info(f"{easycache.name} [verbose] - approx_output_change_rates {len(approx_output_change_rates)}: {approx_output_change_rates}")
         total_steps = len(args[3])-1
-        logging.info(f"{easycache.name} - skipped {easycache.total_steps_skipped}/{total_steps} steps ({total_steps/(total_steps-easycache.total_steps_skipped):.2f}x speedup).")
+        # catch division by zero for log statement; sucks to crash after all sampling is done
+        try:
+            speedup = total_steps/(total_steps-easycache.total_steps_skipped)
+        except ZeroDivisionError:
+            speedup = 1.0
+        logging.info(f"{easycache.name} - skipped {easycache.total_steps_skipped}/{total_steps} steps ({speedup:.2f}x speedup).")
         easycache.reset()
         guider.model_options = orig_model_options