@@ -27,6 +27,11 @@ class Flux(SimpleService):
         },
     }
 
+    OPTIMIZATION_PROMPT = """
+    Clean composition with clear subject hierarchy. Soft natural lighting, accurate proportions, and coherent geometry. 
+    Sharp key details with minimal visual noise and artifacts.
+    """
+
     def calculate_price(self, input_message: Message, version: str) -> Decimal:
         price_map = self.TOKENS_COST[version]
         price = price_map['input_imgs']
@@ -70,17 +75,9 @@ class Flux(SimpleService):
         start_time = time.time()
         version = input_message.info.get('version')
         user_prompt = self.translate_prompt(input_message.content)
-        prompt = f"""
-        {user_prompt}.
-        Clear main subject and coherent scene context.
-        Balanced composition with readable foreground, midground, and background.
-        Natural, consistent lighting with clean shadows and good tonal balance.
-        Accurate proportions, clean geometry, and stable spatial relationships.
-        Crisp important details, clear textures, and minimal visual artifacts.
-        """
         callback_data = dict(
             {
-                'prompt': prompt,
+                'prompt': f"{user_prompt}\n{self.OPTIMIZATION_PROMPT}",
                 'go_fast': False,
                 'output_quality': 100,
                 **input_message.info,
@@ -19,6 +19,10 @@ from payments.selectors.payment_plan_selector import PaymentPlanSelector
 class Fluxpulid(SimpleService):
     TOKEN_COST = Decimal('15.0')
     ENDPOINT = 'bytedance/flux-pulid:8baa7ef2255075b46f4d91cd238c21d31181b3e6a864463f967960bb0112525b'
+    OPTIMIZATION_PROMPT = """
+    Faithful identity match with stable face anatomy. 
+    Soft contrast, clear expression, and realistic skin detail. Artifact-free render and coherent composition.
+    """
 
     @classmethod
     def predict_price(cls, content: str, file_exists: bool, info: dict[str, Any]) -> Decimal | None:
@@ -61,7 +65,7 @@ class Fluxpulid(SimpleService):
         translated_prompt = self.translate_prompt(input_message.content)
         callback_data = dict(
             {
-                'prompt': translated_prompt,
+                'prompt': f"{translated_prompt}\n{self.OPTIMIZATION_PROMPT}",
                 'main_face_image': BytesIO(input_message.file.read()),
                 'output_quality': 100,
                 'output_format': 'png',
@@ -52,6 +52,12 @@ class Gptimage(SimpleService):
             '1024x1536': 1372,
         },
     }
+
+    OPTIMIZATION_PROMPT = """
+    Clean composition and consistent perspective. Natural color harmony, realistic texture detail, and sharp subject focus. 
+    Low visual noise with reliable final quality.
+    """
+
     def __init__(self, store: BaseStore) -> None:
         super().__init__(store)
         self.logger = logging.getLogger(self.__class__.__name__)
@@ -106,7 +112,7 @@ class Gptimage(SimpleService):
         for proxy in Proxy.objects.all():
             moderation = 'low' if self.store.user.account_type == 'regular' else 'auto'
             json_data = {
-                'prompt': input_message.content,
+                'prompt': f"{input_message.content}\n{self.OPTIMIZATION_PROMPT}",
                 'model': 'gpt-image-2',
                 'n': 1,
                 'quality': quality,
@@ -23,6 +23,11 @@ from payments.selectors.payment_plan_selector import PaymentPlanSelector
 class Grok_Image(SimpleService):
     TOKENS_COST = Decimal('4')
 
+    OPTIMIZATION_PROMPT = """
+    Balanced scene layout and clear subject separation. Realistic color balance, soft depth cues, and clean edges. 
+    Consistent details without excessive stylization.
+    """
+
     def calculate_price(self) -> Decimal:
         return self.TOKENS_COST
 
@@ -46,7 +51,7 @@ class Grok_Image(SimpleService):
             raise InsufficientBalance(balance, self.TOKENS_COST)
         callback_data = dict(
             {
-                'prompt': self.translate_prompt(input_message.content),
+                'prompt': f"{self.translate_prompt(input_message.content)}\n{self.OPTIMIZATION_PROMPT}",
                 **input_message.info,
             }
         )
@@ -16,6 +16,12 @@ from ml_model.tasks import replicate_run
 class Seedream(SimpleService):
     PRICE = Decimal('10.5')
 
+    OPTIMIZATION_PROMPT = """
+    Subject: one clear focal subject; same mood as the scene below.
+    Scene: simple background; avoid crowds, clutter, tiny props, dense patterns.
+    Light: one coherent light setup. No text, logos, or watermark in the image.
+    """
+
     @classmethod
     def predict_price(cls, content: str, file_exists: bool, info: dict[str, Any]) -> Decimal | None:
         return cls.PRICE.quantize(Decimal('0.1'), rounding='ROUND_UP')
@@ -45,7 +51,7 @@ class Seedream(SimpleService):
             'match_input_image' if raw_aspect_ratio == 'Исходное изображение' else raw_aspect_ratio
         )
         callback_data = {
-            'prompt': input_message.content,
+            'prompt': f"{input_message.content}\n{self.OPTIMIZATION_PROMPT}",
             'aspect_ratio': aspect_ratio,
             **input_message.info,
         }