qwen3.7-max-previewCompare qwen3.7-max-preview API pricing, supported endpoints, capabilities and access options on Modelsell.
Qwen tokenizer (tiktoken-compat)Scores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis 2026-09-30·Qwen3.7 Max Preview
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Qwen3.7 Max Preview 面向文字对话,适合知识解释、材料分析、指令执行和创意写作。它可以根据受众与目的调整表达,也能把多项限制放在一起考虑,例如在指定篇幅内解释一个概念、按固定结构整理材料,或在既定人物与情节条件下写故事。
写说明文时,可以提供读者已有知识、希望回答的问题,以及必须保留的术语,让模型用合适的例子逐步解释。创作时,给出人物动机、冲突和结尾方向,先讨论大纲,再写正文;修改某段时明确保留哪些情节与语气,便于延续已确认的设定。
这一预览模型仅支持思考模式,会在正式回答前进行推理。需要兼顾逻辑、篇幅、格式与内容约束时,先写清条件优先级,再要求最后检查是否逐项满足。输入与输出都为文字,图片中的内容应先提取成文字材料。
它可结合较长上下文阅读资料,但长输入仍应有清楚组织:给不同材料编号,注明背景、事实和创作设定的区别,要求引用材料的部分能够追溯。思考与正式回复需要共同预留输出空间,长篇任务适合先确认结构,再按章节推进。
把需要依据的材料一并提供,并要求区分已知事实、推断与待确认信息。需要外部数据时,可通过配置的查询或检索工具获取,再将结果传回。模型可以提出工具调用,实际查询由应用执行,最终回复应以返回内容为依据。
例如创作一篇短篇悬疑故事,可输入:
“请先给出大纲,再写一篇约1200字的原创故事。地点是停电的社区图书馆,主角是临时值班员。必须包含一本借阅记录异常的书和一位迟到的读者;谜底来自人物选择,不引入超自然力量。前三分之一埋下两条可回看的线索,结尾解决主要谜团但保留一点余味。不要用大段旁白直接解释人物动机。”
确认大纲后再续写正文,修改时列出要保留的线索与情节。该模型不能通过 enable_thinking=false 关闭思考;接收流式输出时分别处理思考内容和最终正文,并为正文留足输出预算。
/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.
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.
| 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 |
| Supplier | RPM | TPM | RPD |
|---|---|---|---|
| Alibaba | Unlimited | Unlimited | Unlimited |
| official | Unlimited | Unlimited | Unlimited |
No restriction
Compare qwen3.7-max-preview API pricing, supported endpoints, capabilities and access options on Modelsell.
Create an API key with access to qwen3.7-max-preview, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.
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Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.
