@@ -96,7 +96,7 @@ class Chatgpt(SimpleService):
 
     @property
     def neuron_model(self):
-        return NeuronModel.objects.get(title='ChatGPT')
+        return NeuronModel.objects.get(title='ChatGPT 4')
 
     def make(
         self,
@@ -153,7 +153,9 @@ class Chatgpt(SimpleService):
                 get_session_history=lambda _: chat_history,
             )
             llm_input = [SystemMessage(content=user_system_prompt), HumanMessage(content=input_content)]
-            input_tokens, input_embedding_tokens = self._get_input_tokens(file, image, chunks, chat_history, llm_input)
+            input_tokens, input_embedding_tokens = self._get_input_tokens(
+                file, image, chunks, chat_history, llm_input, model_name
+            )
             output_tokens = 0
             self.assert_enough_balance(
                 input_tokens, image_size, model=self.llm.model_name, embedding_tokens=input_embedding_tokens
@@ -427,7 +429,8 @@ class Chatgpt(SimpleService):
         input_tokens: int,
         image_size: tuple | None,
         model: str = 'gpt-3.5-turbo',
-        embedding_tokens: int = 0
+        embedding_tokens: int = 0,
+        output_tokens: int = 0,
     ):
         balance = PaymentPlanSelector(self.store.user).get_current_balance()
         total_tokens = input_tokens
@@ -439,8 +442,9 @@ class Chatgpt(SimpleService):
                 embedding_tokens
                 * self.TOOLS_TOKEN_COSTS[self.EMBEDDING_MODEL_FOR_BILLING]['output']
             )
-        if input_cost > balance:
-            raise InsufficientBalance(balance, input_cost)
+        output_cost = self.TOKENS_COST[model]['output'] * output_tokens
+        if input_cost + output_cost > balance:
+            raise InsufficientBalance(balance, input_cost + output_cost)
 
     def calculate_price(
         self,
@@ -520,7 +524,7 @@ class Chatgpt(SimpleService):
         image_data = {'type': 'image_url', 'image_url': {'url': image_url}}
         return normalized_image, image_size, image_data
 
-    def _get_input_tokens(self, file, image, chunks, chat_history, llm_input):
+    def _get_input_tokens(self, file, image, chunks, chat_history, llm_input, model_name=None):
         input_embedding_tokens = 0
         if file and not image:
             if sum([len(chunk.content) for chunk in chunks]) > 20_000:
@@ -528,7 +532,7 @@ class Chatgpt(SimpleService):
                 input_embedding_tokens = len(chunks) * 600
             else:
                 input_tokens = self.count_text_tokens([*chat_history.messages, *llm_input, *chunks])
-        elif image:
+        elif image and model_name in ('gpt-4o', 'gpt-4o-mini'):
             input_tokens = self.count_text_tokens(llm_input)
         else:
             input_tokens = self.count_text_tokens([*chat_history.messages, *llm_input])
@@ -603,7 +607,12 @@ class Chatgpt(SimpleService):
                 endpoint == 'responses'
                 and (data := resp.json())
                 and data.get('output')
-                and (image := data['output'][0]['result'])
+                and (
+                    image := next(
+                        (item['result'] for item in data['output'] if item.get('result')),
+                        None,
+                    )
+                )
             ):
                 input_tokens = resp.json()['usage']['input_tokens']
                 output_tokens = resp.json()['usage']['output_tokens']
@@ -127,7 +127,7 @@ class Chatgpt_5(Chatgpt):
         chat_history.add_message(HumanMessage(content=input_message.content))
         llm_input = [SystemMessage(content=user_system_prompt), HumanMessage(content=input_content)]
         input_tokens, input_embedding_tokens = self._get_input_tokens(
-            file, image, chunks, chat_history, llm_input
+            file, image, chunks, chat_history, llm_input, model_name
         )
         self.assert_enough_balance(
             input_tokens, image_size, model=model_name, embedding_tokens=input_embedding_tokens
@@ -106,6 +106,12 @@ class Chatgpt_5_4(Chatgpt):
         info = input_message.info.copy()
         model_name = info.pop('version', 'gpt-5.4')
         user_system_prompt = info.pop('system_prompt', '')
+        plan_info = self.store.user.payment_plan
+        is_free_plan = plan_info and plan_info.plan.price <= 0
+        if is_free_plan:
+            info.pop('web_search', None)
+            info.pop('code_interpreter', None)
+            info.pop('verbosity', None)
         input_content = [{'type': 'text', 'text': input_message.content or ''}]
         file = input_message.file
         image = None
@@ -134,10 +140,14 @@ class Chatgpt_5_4(Chatgpt):
         chat_history.add_message(HumanMessage(content=input_message.content))
         llm_input = [SystemMessage(content=user_system_prompt), HumanMessage(content=input_content)]
         input_tokens, input_embedding_tokens = self._get_input_tokens(
-            file, image, chunks, chat_history, llm_input
+            file, image, chunks, chat_history, llm_input, model_name
         )
         self.assert_enough_balance(
-            input_tokens, image_size, model=model_name, embedding_tokens=input_embedding_tokens
+            input_tokens,
+            image_size,
+            model=model_name,
+            embedding_tokens=input_embedding_tokens,
+            output_tokens=500 if is_free_plan else 4000,
         )
         for proxy in Proxy.objects.all():
             system = chat_history.messages.pop(0)
@@ -175,17 +185,20 @@ class Chatgpt_5_4(Chatgpt):
                         'Используй системный промпт. Содержание файла: '
                         f'{"".join(text_chunks)}. Вопрос: {input_message.content}'
                     )
-            json_data = {
-                'model': model_name,
-                'input': messages,
-                'tools': [
+            tools = []
+            if not is_free_plan:
+                tools.append(
                     {
                         'type': 'image_generation',
                         'size': '1024x1024',
                         'quality': 'medium',
                         'model': 'gpt-image-1.5',
                     }
-                ],
+                )
+            json_data = {
+                'model': model_name,
+                'input': messages,
+                'tools': tools,
                 'instructions': (
                     'Форматирование — обязательное требование. Выполняй строго по правилам:\n\n'
                     "1) Используй реальные символы новой строки, не выводи '\\n' как текст — вставляй переносы.\n\n"
@@ -205,7 +218,10 @@ class Chatgpt_5_4(Chatgpt):
                     'добавляй две пустые строки между абзацами и блоками для улучшения читаемости.'
                 ),
             }
-            if reasoning := info.get('reasoning'):
+            if is_free_plan:
+                json_data['max_output_tokens'] = 500
+                json_data['reasoning'] = {'effort': 'none', 'summary': 'auto'}
+            elif reasoning := info.get('reasoning'):
                 reasoning_data = {
                     'Минимальный': 'minimal',
                     'Низкий': 'low',