Qwen3.8-Max
复制成功！
立即体验加入对比
概述
2.4万亿参数MoE旗舰，编程与办公能力全面跃升，可自主编程十数天交付完整项目。胜任法律、金融、设计等数百种专业任务，一次对话端到端交付生产级成果。原生视觉理解贯穿规划、执行与验证全流程，支持超长文档与长视频的深度语义解析。长程任务中自主规划与闭环迭代，持续进化。
输入
图像文本视频
输出
文本
功能
定价
- 输入¥12/M tokens
- 输出¥36/M tokens
- 输入（缓存命中）¥1.5/M tokens
- 输入（Batch File）¥6/M tokens
- 输出（Batch File）¥18/M tokens
- 显式缓存创建¥15/M tokens
- 显式缓存命中¥1/M tokens
- 输入（Batch Chat)限时5折¥12¥6/M tokens
- 输出（Batch Chat)限时5折¥36¥18/M tokens
速率限制与上下文
- 最大输入991K
- 最大输出131K
- 最大输入（思考模式）983K
- 最大输出（思考模式）131K
- 上下文1M
- 最大思维链262K
- TPM每分钟 Token 数5M
内置工具
API 参考
调用API复制成功！
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from openai import OpenAI
import os
client = OpenAI(
# 如果没有配置环境变量，请用阿里云百炼API Key替换：api_key="sk-xxx"
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
messages = [{"role": "user", "content": "你是谁"}]
completion = client.chat.completions.create(
model="qwen3.8-max", # 您可以按需更换为其它深度思考模型
messages=messages,
extra_body={"enable_thinking": True},
stream=True
)
is_answering = False # 是否进入回复阶段
print("\n" + "=" * 20 + "思考过程" + "=" * 20)
for chunk in completion:
if not chunk.choices:
continue
delta = chunk.choices[0].delta
if hasattr(delta, "reasoning_content") and delta.reasoning_content is not None:
if not is_answering:
print(delta.reasoning_content, end="", flush=True)
if hasattr(delta, "content") and delta.content:
if not is_answering:
print("\n" + "=" * 20 + "完整回复" + "=" * 20)
is_answering = True
print(delta.content, end="", flush=True)123456789101112131415161718192021222324252627282930
from openai import OpenAI
import os
client = OpenAI(
# 如果没有配置环境变量，请用阿里云百炼API Key替换：api_key="sk-xxx"
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
messages = [{"role": "user", "content": "你是谁"}]
completion = client.chat.completions.create(
model="qwen3.8-max", # 您可以按需更换为其它深度思考模型
messages=messages,
extra_body={"enable_thinking": True},
stream=True
)
is_answering = False # 是否进入回复阶段
print("\n" + "=" * 20 + "思考过程" + "=" * 20)
for chunk in completion:
if not chunk.choices:
continue
delta = chunk.choices[0].delta
if hasattr(delta, "reasoning_content") and delta.reasoning_content is not None:
if not is_answering:
print(delta.reasoning_content, end="", flush=True)
if hasattr(delta, "content") and delta.content:
if not is_answering:
print("\n" + "=" * 20 + "完整回复" + "=" * 20)
is_answering = True
print(delta.content, end="", flush=True)