diff --git a/backend/app/api/v1/endpoints/config.py b/backend/app/api/v1/endpoints/config.py
index 844bca1..bf1e8f5 100644
--- a/backend/app/api/v1/endpoints/config.py
+++ b/backend/app/api/v1/endpoints/config.py
@@ -239,7 +239,8 @@ async def test_llm_connection(
     current_user: User = Depends(deps.get_current_user),
 ) -> Any:
     """测试LLM连接是否正常"""
-    from app.services.llm.factory import LLMFactory
+    from app.services.llm.factory import LLMFactory, NATIVE_ONLY_PROVIDERS
+    from app.services.llm.adapters import LiteLLMAdapter, BaiduAdapter, MinimaxAdapter, DoubaoAdapter
     from app.services.llm.types import LLMConfig, LLMProvider, LLMRequest, LLMMessage, DEFAULT_MODELS
     
     try:
@@ -278,8 +279,16 @@ async def test_llm_connection(
             max_tokens=50,  # 测试使用较少的token
         )
         
-        # 创建适配器并测试
-        adapter = LLMFactory.create_adapter(config)
+        # 直接创建新的适配器实例（不使用缓存），确保使用最新的配置
+        if provider in NATIVE_ONLY_PROVIDERS:
+            native_adapter_map = {
+                LLMProvider.BAIDU: BaiduAdapter,
+                LLMProvider.MINIMAX: MinimaxAdapter,
+                LLMProvider.DOUBAO: DoubaoAdapter,
+            }
+            adapter = native_adapter_map[provider](config)
+        else:
+            adapter = LiteLLMAdapter(config)
         
         test_request = LLMRequest(
             messages=[
@@ -290,6 +299,13 @@ async def test_llm_connection(
         
         response = await adapter.complete(test_request)
         
+        # 验证响应内容
+        if not response or not response.content:
+            return LLMTestResponse(
+                success=False,
+                message="LLM 返回空响应，请检查 API Key 和配置"
+            )
+        
         return LLMTestResponse(
             success=True,
             message="LLM连接测试成功",
@@ -298,9 +314,32 @@ async def test_llm_connection(
         )
         
     except Exception as e:
+        error_msg = str(e)
+        # 提供更友好的错误信息
+        if "401" in error_msg or "invalid_api_key" in error_msg.lower() or "incorrect api key" in error_msg.lower():
+            return LLMTestResponse(
+                success=False,
+                message="API Key 无效或已过期，请检查后重试"
+            )
+        elif "authentication" in error_msg.lower():
+            return LLMTestResponse(
+                success=False,
+                message="认证失败，请检查 API Key 是否正确"
+            )
+        elif "timeout" in error_msg.lower():
+            return LLMTestResponse(
+                success=False,
+                message="连接超时，请检查网络或 API 地址是否正确"
+            )
+        elif "connection" in error_msg.lower():
+            return LLMTestResponse(
+                success=False,
+                message="无法连接到 API 服务，请检查网络或 API 地址"
+            )
+        
         return LLMTestResponse(
             success=False,
-            message=f"LLM连接测试失败: {str(e)}"
+            message=f"LLM连接测试失败: {error_msg}"
         )
 
 
diff --git a/backend/app/services/llm/adapters/litellm_adapter.py b/backend/app/services/llm/adapters/litellm_adapter.py
index face748..880a476 100644
--- a/backend/app/services/llm/adapters/litellm_adapter.py
+++ b/backend/app/services/llm/adapters/litellm_adapter.py
@@ -102,6 +102,9 @@ class LiteLLMAdapter(BaseLLMAdapter):
         """发送请求到 LiteLLM"""
         import litellm
         
+        # 禁用 LiteLLM 的缓存，确保每次都实际调用 API
+        litellm.cache = None
+        
         # 构建消息
         messages = [{"role": msg.role, "content": msg.content} for msg in request.messages]
 
@@ -130,10 +133,30 @@ class LiteLLMAdapter(BaseLLMAdapter):
             kwargs["frequency_penalty"] = self.config.frequency_penalty
             kwargs["presence_penalty"] = self.config.presence_penalty
 
-        # 调用 LiteLLM
-        response = await litellm.acompletion(**kwargs)
+        try:
+            # 调用 LiteLLM
+            response = await litellm.acompletion(**kwargs)
+        except litellm.exceptions.AuthenticationError as e:
+            raise LLMError(f"API Key 无效或已过期: {str(e)}", self.config.provider, 401)
+        except litellm.exceptions.RateLimitError as e:
+            raise LLMError(f"API 调用频率超限: {str(e)}", self.config.provider, 429)
+        except litellm.exceptions.APIConnectionError as e:
+            raise LLMError(f"无法连接到 API 服务: {str(e)}", self.config.provider)
+        except litellm.exceptions.APIError as e:
+            raise LLMError(f"API 错误: {str(e)}", self.config.provider, getattr(e, 'status_code', None))
+        except Exception as e:
+            # 捕获其他异常并重新抛出
+            error_msg = str(e)
+            if "invalid_api_key" in error_msg.lower() or "incorrect api key" in error_msg.lower():
+                raise LLMError(f"API Key 无效: {error_msg}", self.config.provider, 401)
+            elif "authentication" in error_msg.lower():
+                raise LLMError(f"认证失败: {error_msg}", self.config.provider, 401)
+            raise
 
         # 解析响应
+        if not response:
+            raise LLMError("API 返回空响应", self.config.provider)
+            
         choice = response.choices[0] if response.choices else None
         if not choice:
             raise LLMError("API响应格式异常: 缺少choices字段", self.config.provider)
diff --git a/backend/app/services/llm/factory.py b/backend/app/services/llm/factory.py
index fba107b..8790534 100644
--- a/backend/app/services/llm/factory.py
+++ b/backend/app/services/llm/factory.py
@@ -102,73 +102,117 @@ class LLMFactory:
 
     @classmethod
     def get_available_models(cls, provider: LLMProvider) -> List[str]:
-        """获取提供商的可用模型列表"""
+        """获取提供商的可用模型列表 (2025年最新)"""
         models = {
             LLMProvider.GEMINI: [
+                "gemini-3-pro",
+                "gemini-3.0-deep-think",
                 "gemini-2.5-flash",
                 "gemini-2.5-pro",
-                "gemini-1.5-flash",
-                "gemini-1.5-pro",
+                "gemini-2.5-flash-lite",
+                "gemini-2.5-flash-live-api",
+                "veo-3.1",
+                "veo-3.1-fast",
             ],
             LLMProvider.OPENAI: [
+                "gpt-5",
+                "gpt-5.1",
+                "gpt-5.1-instant",
+                "gpt-5.1-codex-max",
                 "gpt-4o",
                 "gpt-4o-mini",
-                "gpt-4-turbo",
-                "gpt-4",
-                "gpt-3.5-turbo",
-                "o1-preview",
-                "o1-mini",
+                "gpt-4.5",
+                "o4-mini",
+                "o3",
+                "o3-mini",
+                "gpt-oss-120b",
+                "gpt-oss-20b",
             ],
             LLMProvider.CLAUDE: [
-                "claude-3-5-sonnet-20241022",
-                "claude-3-opus-20240229",
-                "claude-3-sonnet-20240229",
-                "claude-3-haiku-20240307",
+                "claude-opus-4.5",
+                "claude-sonnet-4.5",
+                "claude-haiku-4.5",
+                "claude-sonnet-4",
+                "claude-opus-4",
+                "claude-3.7-sonnet",
+                "claude-3.5-sonnet",
+                "claude-3.5-haiku",
+                "claude-3-opus",
             ],
             LLMProvider.QWEN: [
-                "qwen-turbo",
-                "qwen-plus",
-                "qwen-max",
-                "qwen-max-longcontext",
+                "qwen3-max-instruct",
+                "qwen3-235b-a22b",
+                "qwen3-turbo",
+                "qwen3-32b",
+                "qwen3-4b",
+                "qwen3-embedding-8b",
+                "qwen-image",
+                "qwen-vl",
+                "qwen-audio",
             ],
             LLMProvider.DEEPSEEK: [
+                "deepseek-v3.1-terminus",
+                "deepseek-r1-70b",
+                "deepseek-r1-zero",
+                "deepseek-v3.2-exp",
                 "deepseek-chat",
-                "deepseek-coder",
+                "deepseek-reasoner",
+                "deepseek-ocr",
             ],
             LLMProvider.ZHIPU: [
+                "glm-4.6",
+                "glm-4.6-reap-218b",
+                "glm-4.5",
+                "glm-4.5v",
+                "glm-4.5-air-106b",
                 "glm-4-flash",
-                "glm-4",
-                "glm-4-plus",
-                "glm-4-long",
+                "glm-4v-flash",
+                "glm-4.1v-thinking",
             ],
             LLMProvider.MOONSHOT: [
-                "moonshot-v1-8k",
-                "moonshot-v1-32k",
-                "moonshot-v1-128k",
+                "kimi-k2",
+                "kimi-k2-thinking",
+                "kimi-k2-instruct-0905",
+                "kimi-k1.5",
+                "kimi-vl",
+                "kimi-dev-72b",
+                "kimi-researcher",
+                "kimi-linear",
             ],
             LLMProvider.BAIDU: [
-                "ERNIE-3.5-8K",
-                "ERNIE-4.0-8K",
-                "ERNIE-Speed-8K",
+                "ernie-4.5",
+                "ernie-4.5-21b-a3b-thinking",
+                "ernie-4.0-8k",
+                "ernie-3.5-8k",
+                "ernie-vl",
             ],
             LLMProvider.MINIMAX: [
-                "abab6.5-chat",
-                "abab6.5s-chat",
-                "abab5.5-chat",
+                "minimax-m2",
+                "minimax-01-text",
+                "minimax-01-vl",
+                "minimax-m1",
+                "speech-2.6",
+                "hailuo-02",
+                "music-1.5",
             ],
             LLMProvider.DOUBAO: [
-                "doubao-pro-32k",
-                "doubao-pro-128k",
-                "doubao-lite-32k",
+                "doubao-1.6-pro",
+                "doubao-1.5-pro",
+                "doubao-seed-code",
+                "doubao-seed-1.6",
+                "doubao-vision-language",
             ],
             LLMProvider.OLLAMA: [
-                "llama3",
-                "llama3.1",
-                "llama3.2",
-                "codellama",
-                "mistral",
-                "deepseek-coder-v2",
-                "qwen2.5-coder",
+                "llama3.3-70b",
+                "qwen3-8b",
+                "gemma3-27b",
+                "dolphin-3.0-llama3.1-8b",
+                "cogito-v1",
+                "deepseek-r1",
+                "gpt-oss-120b",
+                "llama3.1-405b",
+                "mistral-nemo",
+                "phi-3",
             ],
         }
         return models.get(provider, [])
diff --git a/backend/app/services/llm/types.py b/backend/app/services/llm/types.py
index 50d438f..5db58e0 100644
--- a/backend/app/services/llm/types.py
+++ b/backend/app/services/llm/types.py
@@ -87,19 +87,19 @@ class LLMError(Exception):
         self.original_error = original_error
 
 
-# 各平台默认模型
+# 各平台默认模型 (2025年最新推荐)
 DEFAULT_MODELS: Dict[LLMProvider, str] = {
-    LLMProvider.GEMINI: "gemini-2.5-flash",
-    LLMProvider.OPENAI: "gpt-4o-mini",
-    LLMProvider.CLAUDE: "claude-3-5-sonnet-20241022",
-    LLMProvider.QWEN: "qwen-turbo",
-    LLMProvider.DEEPSEEK: "deepseek-chat",
-    LLMProvider.ZHIPU: "glm-4-flash",
-    LLMProvider.MOONSHOT: "moonshot-v1-8k",
-    LLMProvider.BAIDU: "ERNIE-3.5-8K",
-    LLMProvider.MINIMAX: "abab6.5-chat",
-    LLMProvider.DOUBAO: "doubao-pro-32k",
-    LLMProvider.OLLAMA: "llama3",
+    LLMProvider.GEMINI: "gemini-3-pro",
+    LLMProvider.OPENAI: "gpt-5",
+    LLMProvider.CLAUDE: "claude-sonnet-4.5",
+    LLMProvider.QWEN: "qwen3-max-instruct",
+    LLMProvider.DEEPSEEK: "deepseek-v3.1-terminus",
+    LLMProvider.ZHIPU: "glm-4.6",
+    LLMProvider.MOONSHOT: "kimi-k2",
+    LLMProvider.BAIDU: "ernie-4.5",
+    LLMProvider.MINIMAX: "minimax-m2",
+    LLMProvider.DOUBAO: "doubao-1.6-pro",
+    LLMProvider.OLLAMA: "llama3.3-70b",
 }
 
 
diff --git a/frontend/src/components/system/SystemConfig.tsx b/frontend/src/components/system/SystemConfig.tsx
index 466327a..a8cbfe3 100644
--- a/frontend/src/components/system/SystemConfig.tsx
+++ b/frontend/src/components/system/SystemConfig.tsx
@@ -11,25 +11,25 @@ import {
 import { toast } from "sonner";
 import { api } from "@/shared/api/database";
 
-// LLM 提供商配置 - 简化分类
+// LLM 提供商配置 - 2025年最新
 const LLM_PROVIDERS = [
-  { value: 'openai', label: 'OpenAI GPT', icon: '🟢', category: 'litellm', hint: 'gpt-4o, gpt-4o-mini 等' },
-  { value: 'claude', label: 'Anthropic Claude', icon: '🟣', category: 'litellm', hint: 'claude-3.5-sonnet 等' },
-  { value: 'gemini', label: 'Google Gemini', icon: '🔵', category: 'litellm', hint: 'gemini-1.5-flash 等' },
-  { value: 'deepseek', label: 'DeepSeek', icon: '🔷', category: 'litellm', hint: 'deepseek-chat, deepseek-coder' },
-  { value: 'qwen', label: '通义千问', icon: '🟠', category: 'litellm', hint: 'qwen-turbo, qwen-max 等' },
-  { value: 'zhipu', label: '智谱AI (GLM)', icon: '🔴', category: 'litellm', hint: 'glm-4-flash, glm-4 等' },
-  { value: 'moonshot', label: 'Moonshot (Kimi)', icon: '🌙', category: 'litellm', hint: 'moonshot-v1-8k 等' },
-  { value: 'ollama', label: 'Ollama 本地', icon: '🖥️', category: 'litellm', hint: 'llama3, codellama 等' },
-  { value: 'baidu', label: '百度文心', icon: '📘', category: 'native', hint: 'ERNIE-3.5-8K (需要 API_KEY:SECRET_KEY)' },
-  { value: 'minimax', label: 'MiniMax', icon: '⚡', category: 'native', hint: 'abab6.5-chat 等' },
-  { value: 'doubao', label: '字节豆包', icon: '🎯', category: 'native', hint: 'doubao-pro-32k 等' },
+  { value: 'openai', label: 'OpenAI GPT', icon: '🟢', category: 'litellm', hint: 'gpt-5, gpt-5-mini, o3 等' },
+  { value: 'claude', label: 'Anthropic Claude', icon: '🟣', category: 'litellm', hint: 'claude-sonnet-4.5, claude-opus-4 等' },
+  { value: 'gemini', label: 'Google Gemini', icon: '🔵', category: 'litellm', hint: 'gemini-3-pro, gemini-3-flash 等' },
+  { value: 'deepseek', label: 'DeepSeek', icon: '🔷', category: 'litellm', hint: 'deepseek-v3.1-terminus, deepseek-v3 等' },
+  { value: 'qwen', label: '通义千问', icon: '🟠', category: 'litellm', hint: 'qwen3-max-instruct, qwen3-plus 等' },
+  { value: 'zhipu', label: '智谱AI (GLM)', icon: '🔴', category: 'litellm', hint: 'glm-4.6, glm-4.5-flash 等' },
+  { value: 'moonshot', label: 'Moonshot (Kimi)', icon: '🌙', category: 'litellm', hint: 'kimi-k2, kimi-k1.5 等' },
+  { value: 'ollama', label: 'Ollama 本地', icon: '🖥️', category: 'litellm', hint: 'llama3.3-70b, qwen3-8b 等' },
+  { value: 'baidu', label: '百度文心', icon: '📘', category: 'native', hint: 'ernie-4.5 (需要 API_KEY:SECRET_KEY)' },
+  { value: 'minimax', label: 'MiniMax', icon: '⚡', category: 'native', hint: 'minimax-m2, minimax-m1 等' },
+  { value: 'doubao', label: '字节豆包', icon: '🎯', category: 'native', hint: 'doubao-1.6-pro, doubao-1.5-pro 等' },
 ];
 
 const DEFAULT_MODELS: Record<string, string> = {
-  openai: 'gpt-4o-mini', claude: 'claude-3-5-sonnet-20241022', gemini: 'gemini-2.5-flash',
-  deepseek: 'deepseek-chat', qwen: 'qwen-turbo', zhipu: 'glm-4-flash', moonshot: 'moonshot-v1-8k',
-  ollama: 'llama3', baidu: 'ERNIE-3.5-8K', minimax: 'abab6.5-chat', doubao: 'doubao-pro-32k',
+  openai: 'gpt-5', claude: 'claude-sonnet-4.5', gemini: 'gemini-3-pro',
+  deepseek: 'deepseek-v3.1-terminus', qwen: 'qwen3-max-instruct', zhipu: 'glm-4.6', moonshot: 'kimi-k2',
+  ollama: 'llama3.3-70b', baidu: 'ernie-4.5', minimax: 'minimax-m2', doubao: 'doubao-1.6-pro',
 };
 
 interface SystemConfigData {