阿里云千问发布 Qwen3.6-Max-Preview 预览版

Qwen3.6-Max-Preview: Smarter, Sharper, Still Evolving | Qwen Blog Publication About Try Qwen Chat Qwen3.6-Max-Preview: Smarter, Sharper, Still Evolving April 18, 2026 · 3 min · 622 words · Qwen Team | Translations: 简体中文 QWEN STUDIO DISCORD Following the release of Qwen3.6-Plus , we are sharing an early preview of our next proprietary model: Qwen3.6-Max-Preview . Compared to Qwen3.6-Plus, this preview release brings stronger world knowledge and instruction following , along with significant agentic coding improvements across a wide range of benchmarks. As a preview, the model is still under active development — we are continuing to iterate and expect further gains in subsequent versions. Qwen3.6-Max-Preview is the hosted proprietary model available via Alibaba Cloud Model Studio , featuring: improved agentic coding capability over Qwen3.6-Plus stronger world knowledge and instruction following improved real-world agent and knowledge reliability performance You can chat interactively on Qwen Studio or call via API as qwen3.6-max-preview on Alibaba Cloud Model Studio API (coming soon). Performance # Below we present evaluations of Qwen3.6-Max-Preview against leading frontier models. Compared to Qwen3.6-Plus, the preview release delivers significant improvements in agentic coding (e.g., SkillsBench +9.9, SciCode +6.3, NL2Repo +5.0, Terminal-Bench 2.0 +3.8), stronger world knowledge (SuperGPQA +2.3, QwenChineseBench +5.3), and better instruction following (ToolcallFormatIFBench +2.8). Build with Qwen3.6-Max-Preview # Qwen3.6-Max-Preview is coming soon to Alibaba Cloud Model Studio. Please stand by until we are fully ready. Qwen3.6-Max-Preview is available through the Alibaba Cloud Model Studio API as qwen3.6-max-preview . You can also try it instantly on Qwen Studio . API Usage # This release supports the preserve_thinking feature: preserving thinking content from all preceding turns in messages, which is recommended for agentic tasks . Alibaba Cloud Model Studio # Alibaba Cloud Model Studio supports industry-standard protocols, including chat completions and responses APIs compatible with OpenAI’s specification, as well as an API interface compatible with Anthropic. Example code for chat completions API is provided below: """ Environment variables (per official docs): DASHSCOPE_API_KEY: Your API Key from https://modelstudio.console.alibabacloud.com DASHSCOPE_BASE_URL: (optional) Base URL for compatible-mode API. - Beijing: https://dashscope.aliyuncs.com/compatible-mode/v1 - Singapore: https://dashscope-intl.aliyuncs.com/compatible-mode/v1 - US (Virginia): https://dashscope-us.aliyuncs.com/compatible-mode/v1 DASHSCOPE_MODEL: (optional) Model name; override for different models. """ from openai import OpenAI import os

api_key = os . environ . get ( "DASHSCOPE_API_KEY" ) if not api_key : raise ValueError ( "DASHSCOPE_API_KEY is required. " "Set it via: export DASHSCOPE_API_KEY='your-api-key'" )

client = OpenAI ( api_key = api_key , base_url = os . environ . get ( "DASHSCOPE_BASE_URL" , "https://dashscope-intl.aliyuncs.com/compatible-mode/v1" , ), )

messages = [{ "role" : "user" , "content" : "Introduce vibe coding." }]

model = os . environ . get ( "DASHSCOPE_MODEL" , "qwen3.6-max-preview" , ) completion = client . chat . completions . create ( model = model , messages = messages , extra_body = { "enable_thinking" : True , # "preserve_thinking": True, }, stream = True )

reasoning_content = "" # Full reasoning trace answer_content = "" # Full response is_answering = False # Whether we have entered the answer phase print ( " \n " + "=" * 20 + "Reasoning" + "=" * 20 + " \n " )

for chunk in completion : if not chunk . choices : print ( " \n Usage:" ) print ( chunk . usage ) continue

delta = chunk . choices [ 0 ] . delta

# Collect reasoning content only if hasattr ( delta , "reasoning_content" ) and delta . reasoning_content is not None : if not is_answering : print ( delta . reasoning_content , end = "" , flush = True ) reasoning_content += delta . reasoning_content