Qwen3.6 Max Preview
qwen3.6-max-previewCompare qwen3.6-max-preview API pricing, supported endpoints, capabilities and access options on Modelsell.
- Starting price
- Input / Output · 1M
- Context
- 262.1K
- Maximum input window
- Max output
- 65.5K
- Maximum tokens per response
- Modalities
- →
Pricing by Supplier
Capabilities / Supported modalities
Provider & data privacy
Qwen tokenizer (tiktoken-compat)Performance
Benchmarks
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis 2026-09-30·Qwen3.6 Max Preview
This model is not included in the current benchmark snapshot.
Missing models or measurements are not zero scores.
Benchmark charts preserve the source model selection and reasoning settings. Missing models or measurements are not zero scores, and benchmark cost or speed is not this site’s service commitment.
About Qwen3.6 Max Preview
把复杂需求写成可运行的实现
Qwen3.6 Max Preview 适合需要多步分析的文字与编程任务，重点面向前端开发、代码智能体和较复杂的问题求解。可以从自然语言需求出发，梳理页面结构、交互状态与数据流，再生成代码；也能阅读已有项目片段，分析问题所在并提出修改方案。
比如制作一个预约管理页面，不只要描述“简洁好看”，还可以指定日期筛选、列表分页、取消预约、加载和失败状态，让模型在实现前列出行为规则。已有项目应同时提供技术栈、目录与组件约定，使生成结果更容易融入现有代码。该预览模型接收和输出文字，设计稿或截图中的信息需要先整理为文字要求。
适合怎样的分析与推理？
它可以比较方案取舍、梳理跨文件逻辑，以及解释日志与代码之间的联系。需要深入判断时，保留默认思考模式，并要求最终回答给出关键依据与可验证结论。多项约束同时存在时，先写清优先级与验收标准，减少模型在实现过程中自行选择含糊规则。
如何组织连续开发任务？
通过函数调用，智能体可以向模型提供文件检索、命令执行等工具，按“查看材料、生成修改、获取运行反馈、继续修正”的顺序工作。工具返回的错误和实际输出应完整传回，便于模型依据结果调整。多轮任务也可使用历史思考保留能力，但仍需维护会话材料与已确认结论。
较长的需求与代码应按模块组织，给每轮任务限定清楚的范围。最后要求汇总改了什么、验证了什么、还有哪些未覆盖条件，让交付结果容易复查。
Use cases and prompting
例如实现预约列表，可输入：
“请基于以下 React 项目实现预约管理页。复用现有表格、弹窗和请求封装。日期筛选改变后回到第一页；取消预约成功后更新当前行，失败时保留原状态并显示原因；重复提交期间禁用按钮。先列状态与数据流，再给需要修改的文件和代码，最后给出正常、空列表、请求失败三类验收步骤。”
随后提供项目约定、相关组件与接口返回示例。如接入开发工具，逐步传回真实文件与运行结果；没有工具时，要求模型把待执行的检查明确列出。任务简单且希望直接回复时，可设置 enable_thinking=false。
API access
API documentation
Code samples
/v1/chat/completions| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Replace <YOUR_API_KEY> with the API key from your token settings.
Authentication
All requests must include Authorization: Bearer <TOKEN> header. Anthropic-formatted endpoints accept the x-api-key header instead.
Generate tokens from the Tokens page; you can scope them to specific models, groups, IPs, and rate-limits.
Supported parameters
| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Rate limits
| Supplier | RPM | TPM | RPD |
|---|---|---|---|
| official | Unlimited | Unlimited | Unlimited |
| Alibaba | Unlimited | Unlimited | Unlimited |
No restriction
Frequently asked questions about qwen3.6-max-preview
What is qwen3.6-max-preview?
Compare qwen3.6-max-preview API pricing, supported endpoints, capabilities and access options on Modelsell.
How do I call qwen3.6-max-preview?
Create an API key with access to qwen3.6-max-preview, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.
How is qwen3.6-max-preview priced?
Pricing depends on the selected provider group and the model billing unit. The current input, output, request, or media prices are shown on this page before sign-up.
What is the context window of qwen3.6-max-preview?
The model catalog lists a context window of 262144 tokens. Check the selected endpoint for request limits.
What is the maximum output of qwen3.6-max-preview?
The model catalog lists a maximum output of 65536 tokens. Your request settings may set a lower limit.
How should I evaluate qwen3.6-max-preview for my project?
Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.