BaiLian

Qwen3.8 Max

AlibabaToken-based
Alias:qwen3.8-max
Create API Key

Compare qwen3.8-max API pricing, supported endpoints, capabilities and access options on Modelsell.

textimagevideofunction_callingtoolsstructured_outputjson_modeweb_searchcachingvisionreasoningcontext:1000000
Starting price
Input / Output · 1M
Context
1M
Maximum input window
Modalities
→

Pricing by Supplier

official
官方接口直连
Input$1.8/ 1M
Output$5.3/ 1M
Cache Read$0.22/ 1M
Alibaba
阿里巴巴百炼官方
Input$1.8/ 1M
Output$5.3/ 1M
Cache Read$0.22/ 1M

Capabilities / Supported modalities

ReasoningFunction callingToolsStructured outputJSON modeWeb searchCode interpreter
Input
Output

Provider & data privacy

Provider
Alibaba (Qwen)Docs
Tokenizer
Qwen tokenizer (tiktoken-compat)
License
Tongyi Qianwen LicenseOpen weights
Data retention81 daysNot used for upstream training by default

Performance

Benchmarks

Scores on standardized evaluations. Higher percentages are better — and rank percentile shows

Metrics sourced fromArtificial Analysis 2026-09-30·Qwen3.8 Max

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 Qwen3.8 Max

为复杂问题建立清楚的判断框架

Qwen3.8 Max 是千问系列面向高要求任务的模型,适合多步逻辑推演、代码调试、架构规划和复杂资料分析。遇到多个目标互相牵制的问题,可以让它先整理约束,再比较方案,说明选择依据与仍需验证的条件。

长材料与多模态信息一起分析

模型可结合文字、图片和视频理解任务,输出文本。大型代码项目可以提供模块说明、相关实现与运行画面;业务分析可以提供讨论记录、操作资料和图表,让模型检查不同材料是否相互支持。材料越多,越应明确任务目标、重要性顺序和出处,避免长上下文变成没有主线的资料堆。

思考、工具与结构化结果

Qwen3.8 Max支持思考模式、函数调用、内置工具与结构化输出。应用可以根据任务接入检索、执行或业务工具,让分析连接到实际数据与操作;需要程序处理结果时,提前定义字段、枚举和缺失值规则,减少后续转换成本。

复杂任务适合先产出可讨论的方案,再通过实际结果逐步收敛。要求模型列出反对证据、失败条件和验证方法,有助于避免只给出听起来完整的建议。最终交付应包括结论、依据与执行步骤,方便团队审阅和接续。

Use cases and prompting

架构规划示例

“现有搜索服务需要同时改善响应速度和数据更新及时性。根据下面的架构、查询日志与更新流程,比较缓存、索引优化和异步预计算三种方案。先定义比较标准,再分析依赖、失败条件和实施顺序。不要假设不存在的监控数据,缺失信息单独列出。”

怎样让复杂分析最终能用于决策?

指定比较维度和交付结构,要求推荐方案、依据、取舍、实施步骤与验证条件,避免只列优缺点。

结构化输出能直接交给程序吗?

先约定字段与取值,应用端仍应校验类型、必填项和业务范围。工具返回的数据与模型推断也应明确区分。

API access

API documentation

Code samples

RequestPOST/v1/chat/completions
Example request
Parameters
ParameterTypeDefault / rangeDescription
temperature
number
=10 ~ 2
Sampling temperature; lower is more deterministic
top_p
number
=10 ~ 1
Nucleus sampling probability mass
max_tokens
integer>= 1Maximum 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
integer0 ~ 20Number 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

Generation parameters
ParameterTypeDefault / rangeDescription
temperature
number
=10 ~ 2
Sampling temperature; lower is more deterministic
top_p
number
=10 ~ 1
Nucleus sampling probability mass
max_tokens
integer>= 1Maximum 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
integer0 ~ 20Number 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

SupplierRPMTPMRPD
AlibabaUnlimitedUnlimitedUnlimited
officialUnlimitedUnlimitedUnlimited

No restriction

Frequently asked questions about qwen3.8-max

What is qwen3.8-max?

Compare qwen3.8-max API pricing, supported endpoints, capabilities and access options on Modelsell.

How do I call qwen3.8-max?

Create an API key with access to qwen3.8-max, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.

How is qwen3.8-max 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 qwen3.8-max?

The model catalog lists a context window of 1000000 tokens. Check the selected endpoint for request limits.

How should I evaluate qwen3.8-max for my project?

Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.