
Qwen3 Max / 对话
Compared with the September 23, 2025 version, the newly upgraded Qwen-3 Max seamlessly integrates thinking and non-thinking modes, bringing an all-round obvious performance boost. Its thinking mode supports web search, web content extraction and code interpreter. It can conduct in-depth logical reasoning and call external tools to solve intricate problems more precisely
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Playground 对话
与 AI 模型开启对话,您可以询问任何问题。
AI 生成结果的准确性可能有所不同。
Qwen3 MaxChat with Optional Live Search
Qwen3 Max is a production chat model with streaming defaults, optional enable_search for grounded answers, seed control, and standard sampling for product surfaces.

At a Glance
Qwen3 Max Capabilities
Grounded chat for product and knowledge surfaces.
Optional Live Search
enable_search can ground answers in fresh web results when the task needs current facts.

Streaming Default
stream defaults to true for paint-as-you-go chat UX.

Seed & Sampling
Optional seed plus temperature and top-p for reproducible, tunable replies.

Stop Sequences
Bound generation for parsers and structured product flows.

How It Works
Grounded chat in four steps.
Decide Search Need
Enable enable_search when answers need current facts.
Stream Tokens
Consume SSE for immediate UI paint.
Pin Seed for Eval
Use seed when building regression or golden sets.
Bound Output
Apply stop sequences for structured flows.
Qwen3 Max Domains
Where answers need freshness and control.
Knowledge Assist
Search-grounded answers for support and docs.
Research Chat
Current-events synthesis with streaming UX.
Product Q&A
Grounded product facts for storefronts.
Internal Wikis
Seed-reproducible answers for eval sets.
Prompt Tips
Keep Qwen3 Max answers useful.
Request citations or source names when enable_search is on.
Skip search for rewrites and tone edits to save latency.
Seeds make golden-set comparisons reproducible.
Qwen3 Max Quickstart
Search-aware streaming chat.
curl -X POST "https://api.powertokens.ai/v1/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3-max",
"messages": [
{"role": "user", "content": "What are the latest best practices for prompt caching in production LLM stacks?"}
],
"stream": true,
"temperature": 0.7
}'Technical Specifications
Confirmed parameters and runtime execution protocols.
价格详情
此模型的实际计费根据您在 API 请求中传入的具体参数动态计算。以下是具体的组合及其对应的价格:
| 模态 | 输入积分 | 输出积分 | 输入价格 | 输出价格 | 隐式缓存命中 | 显式缓存命中 | 创建缓存 |
|---|---|---|---|---|---|---|---|
| 0 - 32K | 1,140/ 1M Tokens | 5,700/ 1M Tokens | $1.140 | $5.700 | $0.228 228/ 1M Tokens | $0.114 114/ 1M Tokens | $1.425 1,425/ 1M Tokens |
| 32K - 128K | 2,280/ 1M Tokens | 11,400/ 1M Tokens | $2.280 | $11.400 | $0.456 456/ 1M Tokens | $0.228 228/ 1M Tokens | $2.850 2,850/ 1M Tokens |
| 128K - 256K | 2,850/ 1M Tokens | 14,250/ 1M Tokens | $2.850 | $14.250 | $0.570 570/ 1M Tokens | $0.285 285/ 1M Tokens | $3.563 3,563/ 1M Tokens |
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Frequently Asked Questions
Everything you need to know before integrating this model.
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