diff --git a/config/config.yaml b/config/config.yaml
index 590ef2561..303f4824b 100644
--- a/config/config.yaml
+++ b/config/config.yaml
@@ -63,9 +63,9 @@ SD_T2I_API: "/sdapi/v1/txt2img"
 #PUPPETEER_CONFIG: "./config/puppeteer-config.json"
 #MMDC: "./node_modules/.bin/mmdc"
 
-### for update_costs & calc_usage
-UPDATE_COSTS: false
-CALC_USAGE: false
+
+### for calc_usage
+# CALC_USAGE: false
 
 ### for Research
 MODEL_FOR_RESEARCHER_SUMMARY: gpt-3.5-turbo
diff --git a/metagpt/config.py b/metagpt/config.py
index 792233ab2..fb1aa485c 100644
--- a/metagpt/config.py
+++ b/metagpt/config.py
@@ -76,10 +76,10 @@ class Config(metaclass=Singleton):
             logger.warning("LONG_TERM_MEMORY is True")
         self.max_budget = self._get("MAX_BUDGET", 10.0)
         self.total_cost = 0.0
-        self.puppeteer_config = self._get("PUPPETEER_CONFIG", "")
-        self.mmdc = self._get("MMDC", "mmdc")
-        self.update_costs = self._get("UPDATE_COSTS", True)
-        self.calc_usage = self._get("CALC_USAGE", True)
+
+        self.puppeteer_config = self._get("PUPPETEER_CONFIG","")
+        self.mmdc = self._get("MMDC","mmdc")
+        self.calc_usage = self._get("CALC_USAGE",True)
         self.model_for_researcher_summary = self._get("MODEL_FOR_RESEARCHER_SUMMARY")
         self.model_for_researcher_report = self._get("MODEL_FOR_RESEARCHER_REPORT")
 
diff --git a/metagpt/provider/openai_api.py b/metagpt/provider/openai_api.py
index b4fa8752b..79121c8de 100644
--- a/metagpt/provider/openai_api.py
+++ b/metagpt/provider/openai_api.py
@@ -226,11 +226,16 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
     def _calc_usage(self, messages: list[dict], rsp: str) -> dict:
         usage = {}
         if CONFIG.calc_usage:
-            prompt_tokens = count_message_tokens(messages, self.model)
-            completion_tokens = count_string_tokens(rsp, self.model)
-            usage['prompt_tokens'] = prompt_tokens
-            usage['completion_tokens'] = completion_tokens
-        return usage
+            try:
+                prompt_tokens = count_message_tokens(messages, self.model)
+                completion_tokens = count_string_tokens(rsp, self.model)
+                usage['prompt_tokens'] = prompt_tokens
+                usage['completion_tokens'] = completion_tokens
+                return usage
+            except Exception as e:
+                logger.error("usage calculation failed!", e)
+        else:
+            return usage
 
     async def acompletion_batch(self, batch: list[list[dict]]) -> list[dict]:
         """返回完整JSON"""
@@ -259,10 +264,13 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
         return results
 
     def _update_costs(self, usage: dict):
-        if CONFIG.update_costs:
-            prompt_tokens = int(usage['prompt_tokens'])
-            completion_tokens = int(usage['completion_tokens'])
-            self._cost_manager.update_cost(prompt_tokens, completion_tokens, self.model)
+        if CONFIG.calc_usage:
+            try:
+                prompt_tokens = int(usage['prompt_tokens'])
+                completion_tokens = int(usage['completion_tokens'])
+                self._cost_manager.update_cost(prompt_tokens, completion_tokens, self.model)
+            except Exception as e:
+                logger.error("updating costs failed!", e)
 
     def get_costs(self) -> Costs:
         return self._cost_manager.get_costs()