diff --git a/src/renderer/src/aiCore/clients/__tests__/ApiClientFactory.test.ts b/src/renderer/src/aiCore/clients/__tests__/ApiClientFactory.test.ts
index 172798dc38..5ec3bf6404 100644
--- a/src/renderer/src/aiCore/clients/__tests__/ApiClientFactory.test.ts
+++ b/src/renderer/src/aiCore/clients/__tests__/ApiClientFactory.test.ts
@@ -5,6 +5,7 @@ import { beforeEach, describe, expect, it, vi } from 'vitest'
 import { AihubmixAPIClient } from '../AihubmixAPIClient'
 import { AnthropicAPIClient } from '../anthropic/AnthropicAPIClient'
 import { ApiClientFactory } from '../ApiClientFactory'
+import { AwsBedrockAPIClient } from '../aws/AwsBedrockAPIClient'
 import { GeminiAPIClient } from '../gemini/GeminiAPIClient'
 import { VertexAPIClient } from '../gemini/VertexAPIClient'
 import { NewAPIClient } from '../NewAPIClient'
@@ -54,6 +55,19 @@ vi.mock('../openai/OpenAIResponseAPIClient', () => ({
 vi.mock('../ppio/PPIOAPIClient', () => ({
   PPIOAPIClient: vi.fn().mockImplementation(() => ({}))
 }))
+vi.mock('../aws/AwsBedrockAPIClient', () => ({
+  AwsBedrockAPIClient: vi.fn().mockImplementation(() => ({}))
+}))
+
+// Mock the models config to prevent circular dependency issues
+vi.mock('@renderer/config/models', () => ({
+  findTokenLimit: vi.fn(),
+  isReasoningModel: vi.fn(),
+  SYSTEM_MODELS: {
+    silicon: [],
+    defaultModel: []
+  }
+}))
 
 describe('ApiClientFactory', () => {
   beforeEach(() => {
@@ -144,6 +158,15 @@ describe('ApiClientFactory', () => {
       expect(client).toBeDefined()
     })
 
+    it('should create AwsBedrockAPIClient for aws-bedrock type', () => {
+      const provider = createTestProvider('aws-bedrock', 'aws-bedrock')
+
+      const client = ApiClientFactory.create(provider)
+
+      expect(AwsBedrockAPIClient).toHaveBeenCalledWith(provider)
+      expect(client).toBeDefined()
+    })
+
     // 测试默认情况
     it('should create OpenAIAPIClient as default for unknown type', () => {
       const provider = createTestProvider('unknown', 'unknown-type')
diff --git a/src/renderer/src/aiCore/clients/aws/AwsBedrockAPIClient.ts b/src/renderer/src/aiCore/clients/aws/AwsBedrockAPIClient.ts
index 4e29a0cb5c..d9bd9af9c8 100644
--- a/src/renderer/src/aiCore/clients/aws/AwsBedrockAPIClient.ts
+++ b/src/renderer/src/aiCore/clients/aws/AwsBedrockAPIClient.ts
@@ -2,19 +2,23 @@ import { BedrockClient, ListFoundationModelsCommand, ListInferenceProfilesComman
 import {
   BedrockRuntimeClient,
   ConverseCommand,
-  ConverseStreamCommand,
-  InvokeModelCommand
+  InvokeModelCommand,
+  InvokeModelWithResponseStreamCommand
 } from '@aws-sdk/client-bedrock-runtime'
 import { loggerService } from '@logger'
 import { GenericChunk } from '@renderer/aiCore/middleware/schemas'
 import { DEFAULT_MAX_TOKENS } from '@renderer/config/constant'
+import { findTokenLimit, isReasoningModel } from '@renderer/config/models'
 import {
   getAwsBedrockAccessKeyId,
   getAwsBedrockRegion,
   getAwsBedrockSecretAccessKey
 } from '@renderer/hooks/useAwsBedrock'
+import { getAssistantSettings } from '@renderer/services/AssistantService'
 import { estimateTextTokens } from '@renderer/services/TokenService'
 import {
+  Assistant,
+  EFFORT_RATIO,
   GenerateImageParams,
   MCPCallToolResponse,
   MCPTool,
@@ -23,7 +27,13 @@ import {
   Provider,
   ToolCallResponse
 } from '@renderer/types'
-import { ChunkType, MCPToolCreatedChunk, TextDeltaChunk } from '@renderer/types/chunk'
+import {
+  ChunkType,
+  MCPToolCreatedChunk,
+  TextDeltaChunk,
+  ThinkingDeltaChunk,
+  ThinkingStartChunk
+} from '@renderer/types/chunk'
 import { Message } from '@renderer/types/newMessage'
 import {
   AwsBedrockSdkInstance,
@@ -33,6 +43,7 @@ import {
   AwsBedrockSdkRawOutput,
   AwsBedrockSdkTool,
   AwsBedrockSdkToolCall,
+  AwsBedrockStreamChunk,
   SdkModel
 } from '@renderer/types/sdk'
 import { convertBase64ImageToAwsBedrockFormat } from '@renderer/utils/aws-bedrock-utils'
@@ -103,46 +114,65 @@ export class AwsBedrockAPIClient extends BaseApiClient<
   override async createCompletions(payload: AwsBedrockSdkParams): Promise<AwsBedrockSdkRawOutput> {
     const sdk = await this.getSdkInstance()
 
-    // 转换消息格式到AWS SDK原生格式
+    // 转换消息格式（用于 InvokeModelWithResponseStreamCommand）
     const awsMessages = payload.messages.map((msg) => ({
       role: msg.role,
       content: msg.content.map((content) => {
         if (content.text) {
-          return { text: content.text }
+          return { type: 'text', text: content.text }
         }
         if (content.image) {
+          // 处理图片数据，将 Uint8Array 或数字数组转换为 base64 字符串
+          let base64Data = ''
+          if (content.image.source.bytes) {
+            if (typeof content.image.source.bytes === 'string') {
+              // 如果已经是字符串，直接使用
+              base64Data = content.image.source.bytes
+            } else {
+              // 如果是数组或 Uint8Array，转换为 base64
+              const uint8Array = new Uint8Array(Object.values(content.image.source.bytes))
+              const binaryString = Array.from(uint8Array)
+                .map((byte) => String.fromCharCode(byte))
+                .join('')
+              base64Data = btoa(binaryString)
+            }
+          }
+
           return {
-            image: {
-              format: content.image.format,
-              source: content.image.source
+            type: 'image',
+            source: {
+              type: 'base64',
+              media_type: `image/${content.image.format}`,
+              data: base64Data
             }
           }
         }
         if (content.toolResult) {
           return {
-            toolResult: {
-              toolUseId: content.toolResult.toolUseId,
-              content: content.toolResult.content,
-              status: content.toolResult.status
-            }
+            type: 'tool_result',
+            tool_use_id: content.toolResult.toolUseId,
+            content: content.toolResult.content
           }
         }
         if (content.toolUse) {
           return {
-            toolUse: {
-              toolUseId: content.toolUse.toolUseId,
-              name: content.toolUse.name,
-              input: content.toolUse.input
-            }
+            type: 'tool_use',
+            id: content.toolUse.toolUseId,
+            name: content.toolUse.name,
+            input: content.toolUse.input
           }
         }
-        // 返回符合AWS SDK ContentBlock类型的对象
-        return { text: 'Unknown content type' }
+        return { type: 'text', text: 'Unknown content type' }
       })
     }))
 
     logger.info('Creating completions with model ID:', { modelId: payload.modelId })
 
+    const excludeKeys = ['modelId', 'messages', 'system', 'maxTokens', 'temperature', 'topP', 'stream', 'tools']
+    const additionalParams = Object.keys(payload)
+      .filter((key) => !excludeKeys.includes(key))
+      .reduce((acc, key) => ({ ...acc, [key]: payload[key] }), {})
+
     const commonParams = {
       modelId: payload.modelId,
       messages: awsMessages as any,
@@ -162,10 +192,18 @@ export class AwsBedrockAPIClient extends BaseApiClient<
 
     try {
       if (payload.stream) {
-        const command = new ConverseStreamCommand(commonParams)
+        // 根据模型类型选择正确的 API 格式
+        const requestBody = this.createRequestBodyForModel(commonParams, additionalParams)
+
+        const command = new InvokeModelWithResponseStreamCommand({
+          modelId: commonParams.modelId,
+          body: JSON.stringify(requestBody),
+          contentType: 'application/json',
+          accept: 'application/json'
+        })
+
         const response = await sdk.client.send(command)
-        // 直接返回AWS Bedrock流式响应的异步迭代器
-        return this.createStreamIterator(response)
+        return this.createInvokeModelStreamIterator(response)
       } else {
         const command = new ConverseCommand(commonParams)
         const response = await sdk.client.send(command)
@@ -177,32 +215,236 @@ export class AwsBedrockAPIClient extends BaseApiClient<
     }
   }
 
-  private async *createStreamIterator(response: any): AsyncIterable<AwsBedrockSdkRawChunk> {
-    try {
-      if (response.stream) {
-        for await (const chunk of response.stream) {
-          logger.debug('AWS Bedrock chunk received:', chunk)
+  /**
+   * 根据模型类型创建请求体
+   */
+  private createRequestBodyForModel(commonParams: any, additionalParams: any): any {
+    const modelId = commonParams.modelId.toLowerCase()
 
-          // AWS Bedrock的流式响应格式转换为标准格式
-          if (chunk.contentBlockDelta?.delta?.text) {
-            yield {
-              contentBlockDelta: {
-                delta: { text: chunk.contentBlockDelta.delta.text }
+    // Claude 系列模型使用 Anthropic API 格式
+    if (modelId.includes('claude')) {
+      return {
+        anthropic_version: 'bedrock-2023-05-31',
+        max_tokens: commonParams.inferenceConfig.maxTokens,
+        temperature: commonParams.inferenceConfig.temperature,
+        top_p: commonParams.inferenceConfig.topP,
+        messages: commonParams.messages,
+        ...(commonParams.system && commonParams.system[0]?.text ? { system: commonParams.system[0].text } : {}),
+        ...(commonParams.toolConfig?.tools ? { tools: commonParams.toolConfig.tools } : {}),
+        ...additionalParams
+      }
+    }
+
+    // OpenAI 系列模型
+    if (modelId.includes('gpt') || modelId.includes('openai')) {
+      const messages: any[] = []
+
+      // 添加系统消息
+      if (commonParams.system && commonParams.system[0]?.text) {
+        messages.push({
+          role: 'system',
+          content: commonParams.system[0].text
+        })
+      }
+
+      // 转换消息格式
+      for (const message of commonParams.messages) {
+        const content: any[] = []
+        for (const part of message.content) {
+          if (part.text) {
+            content.push({ type: 'text', text: part.text })
+          } else if (part.image) {
+            content.push({
+              type: 'image_url',
+              image_url: {
+                url: `data:image/${part.image.format};base64,${part.image.source.bytes}`
+              }
+            })
+          }
+        }
+        messages.push({
+          role: message.role,
+          content: content.length === 1 && content[0].type === 'text' ? content[0].text : content
+        })
+      }
+
+      const baseBody: any = {
+        model: commonParams.modelId,
+        messages: messages,
+        max_tokens: commonParams.inferenceConfig.maxTokens,
+        temperature: commonParams.inferenceConfig.temperature,
+        top_p: commonParams.inferenceConfig.topP,
+        stream: true,
+        ...(commonParams.toolConfig?.tools ? { tools: commonParams.toolConfig.tools } : {})
+      }
+
+      // OpenAI 模型的 thinking 参数格式
+      if (additionalParams.reasoning_effort) {
+        baseBody.reasoning_effort = additionalParams.reasoning_effort
+        delete additionalParams.reasoning_effort
+      }
+
+      return {
+        ...baseBody,
+        ...additionalParams
+      }
+    }
+
+    // Llama 系列模型
+    if (modelId.includes('llama')) {
+      const baseBody: any = {
+        prompt: this.convertMessagesToPrompt(commonParams.messages, commonParams.system),
+        max_gen_len: commonParams.inferenceConfig.maxTokens,
+        temperature: commonParams.inferenceConfig.temperature,
+        top_p: commonParams.inferenceConfig.topP
+      }
+
+      // Llama 模型的 thinking 参数格式
+      if (additionalParams.thinking_mode) {
+        baseBody.thinking_mode = additionalParams.thinking_mode
+        delete additionalParams.thinking_mode
+      }
+
+      return {
+        ...baseBody,
+        ...additionalParams
+      }
+    }
+
+    // Amazon Titan 系列模型
+    if (modelId.includes('titan')) {
+      const textGenerationConfig: any = {
+        maxTokenCount: commonParams.inferenceConfig.maxTokens,
+        temperature: commonParams.inferenceConfig.temperature,
+        topP: commonParams.inferenceConfig.topP
+      }
+
+      // 将 thinking 相关参数添加到 textGenerationConfig 中
+      if (additionalParams.thinking) {
+        textGenerationConfig.thinking = additionalParams.thinking
+        delete additionalParams.thinking
+      }
+
+      return {
+        inputText: this.convertMessagesToPrompt(commonParams.messages, commonParams.system),
+        textGenerationConfig: {
+          ...textGenerationConfig,
+          ...Object.keys(additionalParams).reduce((acc, key) => {
+            if (['thinking_tokens', 'reasoning_mode'].includes(key)) {
+              acc[key] = additionalParams[key]
+              delete additionalParams[key]
+            }
+            return acc
+          }, {} as any)
+        },
+        ...additionalParams
+      }
+    }
+
+    // Cohere Command 系列模型
+    if (modelId.includes('cohere') || modelId.includes('command')) {
+      const baseBody: any = {
+        message: this.convertMessagesToPrompt(commonParams.messages, commonParams.system),
+        max_tokens: commonParams.inferenceConfig.maxTokens,
+        temperature: commonParams.inferenceConfig.temperature,
+        p: commonParams.inferenceConfig.topP
+      }
+
+      // Cohere 模型的 thinking 参数格式
+      if (additionalParams.thinking) {
+        baseBody.thinking = additionalParams.thinking
+        delete additionalParams.thinking
+      }
+      if (additionalParams.reasoning_tokens) {
+        baseBody.reasoning_tokens = additionalParams.reasoning_tokens
+        delete additionalParams.reasoning_tokens
+      }
+
+      return {
+        ...baseBody,
+        ...additionalParams
+      }
+    }
+
+    // 默认使用通用格式
+    const baseBody: any = {
+      prompt: this.convertMessagesToPrompt(commonParams.messages, commonParams.system),
+      max_tokens: commonParams.inferenceConfig.maxTokens,
+      temperature: commonParams.inferenceConfig.temperature,
+      top_p: commonParams.inferenceConfig.topP
+    }
+
+    return {
+      ...baseBody,
+      ...additionalParams
+    }
+  }
+
+  /**
+   * 将消息转换为简单的 prompt 格式
+   */
+  private convertMessagesToPrompt(messages: any[], system?: any[]): string {
+    let prompt = ''
+
+    // 添加系统消息
+    if (system && system[0]?.text) {
+      prompt += `System: ${system[0].text}\n\n`
+    }
+
+    // 添加对话消息
+    for (const message of messages) {
+      const role = message.role === 'assistant' ? 'Assistant' : 'Human'
+      let content = ''
+
+      for (const part of message.content) {
+        if (part.text) {
+          content += part.text
+        } else if (part.image) {
+          content += '[Image]'
+        }
+      }
+
+      prompt += `${role}: ${content}\n\n`
+    }
+
+    prompt += 'Assistant:'
+    return prompt
+  }
+
+  private async *createInvokeModelStreamIterator(response: any): AsyncIterable<AwsBedrockSdkRawChunk> {
+    try {
+      if (response.body) {
+        for await (const event of response.body) {
+          if (event.chunk) {
+            const chunk: AwsBedrockStreamChunk = JSON.parse(new TextDecoder().decode(event.chunk.bytes))
+
+            // 转换为标准格式
+            if (chunk.type === 'content_block_delta') {
+              yield {
+                contentBlockDelta: {
+                  delta: chunk.delta,
+                  contentBlockIndex: chunk.index
+                }
+              }
+            } else if (chunk.type === 'message_start') {
+              yield { messageStart: chunk }
+            } else if (chunk.type === 'message_stop') {
+              yield { messageStop: chunk }
+            } else if (chunk.type === 'content_block_start') {
+              yield {
+                contentBlockStart: {
+                  start: chunk.content_block,
+                  contentBlockIndex: chunk.index
+                }
+              }
+            } else if (chunk.type === 'content_block_stop') {
+              yield {
+                contentBlockStop: {
+                  contentBlockIndex: chunk.index
+                }
               }
             }
           }
-
-          if (chunk.messageStart) {
-            yield { messageStart: chunk.messageStart }
-          }
-
-          if (chunk.messageStop) {
-            yield { messageStop: chunk.messageStop }
-          }
-
-          if (chunk.metadata) {
-            yield { metadata: chunk.metadata }
-          }
         }
       }
     } catch (error) {
@@ -485,6 +727,38 @@ export class AwsBedrockAPIClient extends BaseApiClient<
           }
         }
 
+        // 获取推理预算token（对所有支持推理的模型）
+        const budgetTokens = this.getBudgetToken(assistant, model)
+
+        // 构建基础自定义参数
+        const customParams: Record<string, any> =
+          coreRequest.callType === 'chat' ? this.getCustomParameters(assistant) : {}
+
+        // 根据模型类型添加 thinking 参数
+        if (budgetTokens) {
+          const modelId = model.id.toLowerCase()
+
+          if (modelId.includes('claude')) {
+            // Claude 模型使用 Anthropic 格式
+            customParams.thinking = { type: 'enabled', budget_tokens: budgetTokens }
+          } else if (modelId.includes('gpt') || modelId.includes('openai')) {
+            // OpenAI 模型格式
+            customParams.reasoning_effort = assistant?.settings?.reasoning_effort
+          } else if (modelId.includes('llama')) {
+            // Llama 模型格式
+            customParams.thinking_mode = true
+            customParams.thinking_tokens = budgetTokens
+          } else if (modelId.includes('titan')) {
+            // Titan 模型格式
+            customParams.thinking = { enabled: true }
+            customParams.thinking_tokens = budgetTokens
+          } else if (modelId.includes('cohere') || modelId.includes('command')) {
+            // Cohere 模型格式
+            customParams.thinking = { enabled: true }
+            customParams.reasoning_tokens = budgetTokens
+          }
+        }
+
         const payload: AwsBedrockSdkParams = {
           modelId: model.id,
           messages:
@@ -497,9 +771,7 @@ export class AwsBedrockAPIClient extends BaseApiClient<
           topP: this.getTopP(assistant, model),
           stream: streamOutput !== false,
           tools: tools.length > 0 ? tools : undefined,
-          // 只在对话场景下应用自定义参数，避免影响翻译、总结等其他业务逻辑
-          // 注意：用户自定义参数总是应该覆盖其他参数
-          ...(coreRequest.callType === 'chat' ? this.getCustomParameters(assistant) : {})
+          ...customParams
         }
 
         const timeout = this.getTimeout(model)
@@ -511,6 +783,7 @@ export class AwsBedrockAPIClient extends BaseApiClient<
   getResponseChunkTransformer(): ResponseChunkTransformer<AwsBedrockSdkRawChunk> {
     return () => {
       let hasStartedText = false
+      let hasStartedThinking = false
       let accumulatedJson = ''
       const toolCalls: Record<number, AwsBedrockSdkToolCall> = {}
 
@@ -570,6 +843,24 @@ export class AwsBedrockAPIClient extends BaseApiClient<
             } as TextDeltaChunk)
           }
 
+          // 处理thinking增量
+          if (
+            rawChunk.contentBlockDelta?.delta?.type === 'thinking_delta' &&
+            rawChunk.contentBlockDelta?.delta?.thinking
+          ) {
+            if (!hasStartedThinking) {
+              controller.enqueue({
+                type: ChunkType.THINKING_START
+              } as ThinkingStartChunk)
+              hasStartedThinking = true
+            }
+
+            controller.enqueue({
+              type: ChunkType.THINKING_DELTA,
+              text: rawChunk.contentBlockDelta.delta.thinking
+            } as ThinkingDeltaChunk)
+          }
+
           // 处理内容块停止事件 - 参考 Anthropic 的 content_block_stop 处理
           if (rawChunk.contentBlockStop) {
             const blockIndex = rawChunk.contentBlockStop.contentBlockIndex || 0
@@ -708,4 +999,49 @@ export class AwsBedrockAPIClient extends BaseApiClient<
   extractMessagesFromSdkPayload(sdkPayload: AwsBedrockSdkParams): AwsBedrockSdkMessageParam[] {
     return sdkPayload.messages || []
   }
+
+  /**
+   * 获取 AWS Bedrock 的推理工作量预算token
+   * @param assistant - The assistant
+   * @param model - The model
+   * @returns The budget tokens for reasoning effort
+   */
+  private getBudgetToken(assistant: Assistant, model: Model): number | undefined {
+    try {
+      if (!isReasoningModel(model)) {
+        return undefined
+      }
+
+      const { maxTokens } = getAssistantSettings(assistant)
+      const reasoningEffort = assistant?.settings?.reasoning_effort
+
+      if (reasoningEffort === undefined) {
+        return undefined
+      }
+
+      const effortRatio = EFFORT_RATIO[reasoningEffort]
+      const tokenLimits = findTokenLimit(model.id)
+
+      if (tokenLimits) {
+        // 使用模型特定的 token 限制
+        const budgetTokens = Math.max(
+          1024,
+          Math.floor(
+            Math.min(
+              (tokenLimits.max - tokenLimits.min) * effortRatio + tokenLimits.min,
+              (maxTokens || DEFAULT_MAX_TOKENS) * effortRatio
+            )
+          )
+        )
+        return budgetTokens
+      } else {
+        // 对于没有特定限制的模型，使用简化计算
+        const budgetTokens = Math.max(1024, Math.floor((maxTokens || DEFAULT_MAX_TOKENS) * effortRatio))
+        return budgetTokens
+      }
+    } catch (error) {
+      logger.warn('Failed to calculate budget tokens for reasoning effort:', error as Error)
+      return undefined
+    }
+  }
 }
diff --git a/src/renderer/src/types/sdk.ts b/src/renderer/src/types/sdk.ts
index a5413e54fb..36608ab9fe 100644
--- a/src/renderer/src/types/sdk.ts
+++ b/src/renderer/src/types/sdk.ts
@@ -162,6 +162,7 @@ export interface AwsBedrockSdkParams {
   topP?: number
   stream?: boolean
   tools?: AwsBedrockSdkTool[]
+  [key: string]: any // Allow any additional custom parameters
 }
 
 export interface AwsBedrockSdkMessageParam {
@@ -206,6 +207,22 @@ export interface AwsBedrockSdkMessageParam {
   }>
 }
 
+export interface AwsBedrockStreamChunk {
+  type: string
+  delta?: {
+    text?: string
+    toolUse?: { input?: string }
+    type?: string
+    thinking?: string
+  }
+  index?: number
+  content_block?: any
+  usage?: {
+    inputTokens?: number
+    outputTokens?: number
+  }
+}
+
 export interface AwsBedrockSdkRawChunk {
   contentBlockStart?: {
     start?: {
@@ -222,6 +239,8 @@ export interface AwsBedrockSdkRawChunk {
       toolUse?: {
         input?: string
       }
+      type?: string // 支持 'thinking_delta' 等类型
+      thinking?: string // 支持 thinking 内容
     }
     contentBlockIndex?: number
   }