diff --git a/diffsynth/pipelines/sd3_image.py b/diffsynth/pipelines/sd3_image.py
index e6e72e9..9a4109e 100644
--- a/diffsynth/pipelines/sd3_image.py
+++ b/diffsynth/pipelines/sd3_image.py
@@ -59,9 +59,9 @@ class SD3ImagePipeline(BasePipeline):
         return image
     
 
-    def encode_prompt(self, prompt, positive=True):
+    def encode_prompt(self, prompt, positive=True, t5_sequence_length=77):
         prompt_emb, pooled_prompt_emb = self.prompter.encode_prompt(
-            prompt, device=self.device, positive=positive
+            prompt, device=self.device, positive=positive, t5_sequence_length=t5_sequence_length
         )
         return {"prompt_emb": prompt_emb, "pooled_prompt_emb": pooled_prompt_emb}
     
@@ -84,6 +84,7 @@ class SD3ImagePipeline(BasePipeline):
         height=1024,
         width=1024,
         num_inference_steps=20,
+        t5_sequence_length=77,
         tiled=False,
         tile_size=128,
         tile_stride=64,
@@ -109,9 +110,9 @@ class SD3ImagePipeline(BasePipeline):
 
         # Encode prompts
         self.load_models_to_device(['text_encoder_1', 'text_encoder_2', 'text_encoder_3'])
-        prompt_emb_posi = self.encode_prompt(prompt, positive=True)
-        prompt_emb_nega = self.encode_prompt(negative_prompt, positive=False)
-        prompt_emb_locals = [self.encode_prompt(prompt_local) for prompt_local in local_prompts]
+        prompt_emb_posi = self.encode_prompt(prompt, positive=True, t5_sequence_length=t5_sequence_length)
+        prompt_emb_nega = self.encode_prompt(negative_prompt, positive=False, t5_sequence_length=t5_sequence_length)
+        prompt_emb_locals = [self.encode_prompt(prompt_local, t5_sequence_length=t5_sequence_length) for prompt_local in local_prompts]
 
         # Denoise
         self.load_models_to_device(['dit'])
diff --git a/diffsynth/prompters/sd3_prompter.py b/diffsynth/prompters/sd3_prompter.py
index 73e05b7..ecf9bca 100644
--- a/diffsynth/prompters/sd3_prompter.py
+++ b/diffsynth/prompters/sd3_prompter.py
@@ -67,7 +67,8 @@ class SD3Prompter(BasePrompter):
         self,
         prompt,
         positive=True,
-        device="cuda"
+        device="cuda",
+        t5_sequence_length=77,
     ):
         prompt = self.process_prompt(prompt, positive=positive)
         
@@ -77,9 +78,9 @@ class SD3Prompter(BasePrompter):
 
         # T5
         if self.text_encoder_3 is None:
-            prompt_emb_3 = torch.zeros((prompt_emb_1.shape[0], 256, 4096), dtype=prompt_emb_1.dtype, device=device)
+            prompt_emb_3 = torch.zeros((prompt_emb_1.shape[0], t5_sequence_length, 4096), dtype=prompt_emb_1.dtype, device=device)
         else:
-            prompt_emb_3 = self.encode_prompt_using_t5(prompt, self.text_encoder_3, self.tokenizer_3, 256, device)
+            prompt_emb_3 = self.encode_prompt_using_t5(prompt, self.text_encoder_3, self.tokenizer_3, t5_sequence_length, device)
             prompt_emb_3 = prompt_emb_3.to(prompt_emb_1.dtype) # float32 -> float16
 
         # Merge