@@ -85,7 +85,7 @@ class OpenrouterAdapter:
                             )
                             continue
 
-                if not input_tokens or not output_tokens:
+                if not input_tokens and not output_tokens:
                     logger.error(f'Opernrouter failed get data about tokens for model {model_name}')
                     input_tokens, output_tokens = cls._fallback_tokenize(
                         model_name, messages, content + reasoning
@@ -2,6 +2,7 @@ from ml_model.services.chatgpt import Chatgpt
 from ml_model.services.chatgpt_5 import Chatgpt_5
 from ml_model.services.chatgpt_5_4 import Chatgpt_5_4
 from ml_model.services.chatgpt_5_5 import Chatgpt_5_5
+from ml_model.services.chatgpt_5_6 import Chatgpt_5_6
 from ml_model.services.claude import Claude
 from ml_model.services.codellama import Codellama
 from ml_model.services.dalle import Dalle
@@ -22,6 +22,7 @@ from ml_model.exceptions import (
     CorruptedFileError,
     FileExtensionNotSupported,
     InvalidParameterError,
+    ModelVersionNotAvailable,
     PaidPlanRequiredError,
 )
 from ml_model.services import Chatgpt
@@ -53,6 +54,8 @@ class Chatgpt_5_5(Chatgpt, StreamSimpleService, OpenAIStreamMixin):
         },
     }
 
+    BASE_VERSION = 'gpt-5.5'
+
     TOKEN_LIMITS = {'gpt-5.5': 1_050_000 // 2}
 
     FORMATION_INSTRUCTIONS = (
@@ -211,7 +214,7 @@ class Chatgpt_5_5(Chatgpt, StreamSimpleService, OpenAIStreamMixin):
 
         try:
             for proxy in Proxy.objects.all():
-                json_data, predicted_input_tokens = self._build_payload(proxy, input_message, ctx)
+                json_data, predicted_input_tokens = self._build_payload(proxy, input_message, ctx, include_image_tool=False)
                 model_name = ctx['model_name']
                 self.logger.info(
                     f'Predicted input tokens (responses/input_tokens) для {model_name} - {predicted_input_tokens}'
@@ -261,10 +264,14 @@ class Chatgpt_5_5(Chatgpt, StreamSimpleService, OpenAIStreamMixin):
         proxy: Proxy,
         input_message: Message,
         ctx: dict[str, Any],
+        *,
+        include_image_tool: bool = True
     ) -> tuple[dict[str, Any], int]:
         if not ctx:
-            model_name = 'gpt-5.5'
             info = input_message.info.copy()
+            model_name = info.get('version', self.BASE_VERSION)
+            if model_name is None or model_name not in self.TOKENS_COST:
+                raise ModelVersionNotAvailable(model_name, self.TOKENS_COST)
             user_system_prompt = info.pop('system_prompt', '')
             file = input_message.file
             image = None
@@ -361,7 +368,7 @@ class Chatgpt_5_5(Chatgpt, StreamSimpleService, OpenAIStreamMixin):
             'instructions': self.FORMATION_INSTRUCTIONS,
             'tools': [],
         }
-        if ctx['has_full_access']:
+        if ctx['has_full_access'] and include_image_tool:
             json_data['tools'].append(
                 {
                     'type': 'image_generation',
@@ -435,7 +442,7 @@ class Chatgpt_5_5(Chatgpt, StreamSimpleService, OpenAIStreamMixin):
             + ctx['predict_embedding_tokens']
             * self.TOOLS_TOKEN_COSTS[self.EMBEDDING_MODEL_FOR_BILLING]['output']
         )
-        if ctx['has_full_access']:
+        if ctx['has_full_access'] and include_image_tool:
             predicted_input_price += self.TOKENS_COST[model_name]['generated_image']
         max_output_tokens = max(
             int(
@@ -0,0 +1,62 @@
+from decimal import Decimal
+
+from ml_model.services import Chatgpt_5_5
+
+
+class Chatgpt_5_6(Chatgpt_5_5):
+    TOKENS_COST = {
+        'gpt-5.6-sol': {
+            'input': Decimal('0.0025'),  # $5 / 1M tokens
+            'output': Decimal('0.015'),  # $30 / 1M tokens
+            'web_search': {
+                'low': Decimal('5'),  # 1 call
+                'medium': Decimal('5'),  # 1 call
+                'high': Decimal('5'),  # 1 call
+            },
+            'code_interpreter': Decimal('15'),  # 1 call
+            'generated_image': Decimal('10.2'),
+        },
+        'gpt-5.6-luna': {
+            'input': Decimal('0.0005'),  # $1 / 1M tokens
+            'output': Decimal('0.003'),  # $6 / 1M tokens
+            'web_search': {
+                'low': Decimal('5'),  # 1 call
+                'medium': Decimal('5'),  # 1 call
+                'high': Decimal('5'),  # 1 call
+            },
+            'code_interpreter': Decimal('15'),  # 1 call
+            'generated_image': Decimal('10.2'),
+        },
+        'gpt-5.6-terra': {
+            'input': Decimal('0.00125'),  # $2.5 / 1M tokens
+            'output': Decimal('0.0075'),  # $15 / 1M tokens
+            'web_search': {
+                'low': Decimal('5'),  # 1 call
+                'medium': Decimal('5'),  # 1 call
+                'high': Decimal('5'),  # 1 call
+            },
+            'code_interpreter': Decimal('15'),  # 1 call
+            'generated_image': Decimal('10.2'),
+        },
+    }
+
+    BASE_VERSION = 'gpt-5.6-luna'
+
+    BASE_SYSTEM = (
+        'You are an analytical assistant optimized for GPT-5.6.\n'
+        'Provide accurate, evidence-based, and practical answers.\n\n'
+        'Guidelines:\n'
+        '- Never fabricate facts or technical behavior\n'
+        '- Distinguish facts from assumptions and uncertainty\n'
+        '- Use available retrieved evidence when relevant\n'
+        '- Prefer official documentation and primary sources\n'
+        '- Lead with the conclusion, then include supporting evidence and material caveats\n'
+        '- Mention limitations only when they affect the answer\n'
+        '- Avoid unnecessary repetition or speculative discussion'
+    )
+
+    TOKEN_LIMITS = {
+        'gpt-5.6-sol': 1_050_000 // 2,
+        'gpt-5.6-luna': 1_050_000 // 2,
+        'gpt-5.6-terra': 1_050_000 // 2,
+    }