diff --git a/extensions-builtin/Lora/extra_networks_lora.py b/extensions-builtin/Lora/extra_networks_lora.py
index 1d319d0b6..bba57943c 100644
--- a/extensions-builtin/Lora/extra_networks_lora.py
+++ b/extensions-builtin/Lora/extra_networks_lora.py
@@ -64,6 +64,10 @@ class ExtraNetworkLora(extra_networks.ExtraNetwork):
             shared.log.debug(f"Load network: type=LoRA tags={all_tags} max={shared.opts.lora_apply_tags} apply")
             all_tags = ', '.join(all_tags)
             p.extra_generation_params["LoRA tags"] = all_tags
+            if '_tags_' in p.prompt:
+                p.prompt = p.prompt.replace('_tags_', all_tags)
+            else:
+                p.prompt = f"{p.prompt}, {all_tags}"
             if p.all_prompts is not None:
                 for i in range(len(p.all_prompts)):
                     if '_tags_' in p.all_prompts[i]:
diff --git a/modules/processing.py b/modules/processing.py
index 6e85999d0..c26668763 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -250,6 +250,9 @@ def process_init(p: StableDiffusionProcessing):
             p.all_subseeds = [int(subseed) + x for x in range(len(p.all_prompts))]
     if reset_prompts:
         p.all_prompts, p.all_negative_prompts = shared.prompt_styles.apply_styles_to_prompts(p.all_prompts, p.all_negative_prompts, p.styles, p.all_seeds)
+        p.prompts = p.all_prompts[p.iteration * p.batch_size:(p.iteration+1) * p.batch_size]
+        p.negative_prompts = p.all_negative_prompts[p.iteration * p.batch_size:(p.iteration+1) * p.batch_size]
+
 
 def process_images_inner(p: StableDiffusionProcessing) -> Processed:
     """this is the main loop that both txt2img and img2img use; it calls func_init once inside all the scopes and func_sample once per batch"""
diff --git a/modules/processing_diffusers.py b/modules/processing_diffusers.py
index 3a8f5d2c8..22293fb02 100644
--- a/modules/processing_diffusers.py
+++ b/modules/processing_diffusers.py
@@ -379,6 +379,8 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
         shared.sd_model = sd_models.set_diffuser_pipe(shared.sd_model, sd_models.DiffusersTaskType.INPAINTING) # force pipeline
         if len(getattr(p, 'init_images', [])) == 0:
             p.init_images = [TF.to_pil_image(torch.rand((3, getattr(p, 'height', 512), getattr(p, 'width', 512))))]
+    p.prompts = p.all_prompts[p.iteration * p.batch_size:(p.iteration+1) * p.batch_size]
+    p.negative_prompts = p.all_negative_prompts[p.iteration * p.batch_size:(p.iteration+1) * p.batch_size]
 
     sd_models.move_model(shared.sd_model, devices.device)
     sd_models_compile.openvino_recompile_model(p, hires=False, refiner=False) # recompile if a parameter changes
diff --git a/scripts/xyz_grid_shared.py b/scripts/xyz_grid_shared.py
index f4474d60b..586070658 100644
--- a/scripts/xyz_grid_shared.py
+++ b/scripts/xyz_grid_shared.py
@@ -207,10 +207,8 @@ def apply_lora(p, x, xs):
         return
     x = os.path.basename(x)
     p.prompt = p.prompt + f" <lora:{x}:{shared.opts.extra_networks_default_multiplier}>"
-    if p.all_prompts is not None:
-        p.all_prompts = len(p.all_prompts) * [p.prompt]
-    if p.all_negative_prompts is not None:
-        p.all_negative_prompts = len(p.all_negative_prompts) * [p.prompt]
+    p.all_prompts = None
+    p.all_negative_prompts = None
     shared.log.debug(f'XYZ grid apply LoRA: "{x}"')