AI 模型情报

Qwen 3.6 Max Preview

vercel/3-6-max-preview

出品方: vercel · 系列: qwen · 发布 2026-04-20

⚠ 本模型为社区微调 / 衍生版本,非厂商官方发布。

$1.30
输入 / 1M token
$7.80
输出 / 1M token
240K
上下文长度
64K
最大输出

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

能力清单

工具调用推理? 结构化输出附件开放权重温度可调
支持模态: 输入 text, image, pdf · 输出 text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding59
  • Tool calling40/40
  • Structured output0/20
  • Reasoning10/10
  • Context window (100K → 1M)8/20
  • Provider availability1/10
Agents66
  • Tool calling35/35
  • Structured output0/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability1/10
JSON / structured output32
  • Structured output / JSON mode0/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume2/20
Cost efficiency44
  • Headline price (log-scaled)39/95
  • Has prompt-cache pricing5/5
Long context59
  • Context window (100K → 2M)49/90
  • Has published price for full window10/10
Vision82
  • Accepts image input50/50
  • Context window (10K → 1M)21/30
  • Has published price10/10
  • Provider availability1/10
Production-readiness50
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)0/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$10.40
$0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$20.80
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$6.50
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$18.20
$0.02 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$20.28
$0.02 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

定价详情

推荐定价来自 vercel · alibaba/qwen-3.6-max-preview

$1.30
输入
$7.80
输出
$0.260
缓存读
$1.63
缓存写

在 1 家渠道可用

服务商服务商模型 ID输入 / 1M输出 / 1M上下文发布日期
Vercel AI Gateway
vercel
alibaba/qwen-3.6-max-preview$1.30$7.80240K2026-04-20

Frequently asked questions

How much does Qwen 3.6 Max Preview cost?

Qwen 3.6 Max Preview costs $1.30 per 1M input tokens and $7.80 per 1M output tokens, sourced from vercel. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Qwen 3.6 Max Preview?

Qwen 3.6 Max Preview has a context window of 240K tokens, with a max output of 64K tokens per reply. This is the total combined size of prompt + completion.

Does Qwen 3.6 Max Preview support tool calling?

Yes. Qwen 3.6 Max Preview supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Does Qwen 3.6 Max Preview support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for Qwen 3.6 Max Preview in our data source. Verify with vercel's official documentation before relying on it in production.

Can Qwen 3.6 Max Preview accept image input?

Yes. Qwen 3.6 Max Preview accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check vercel's docs for the exact rule.

Is Qwen 3.6 Max Preview open-weight?

Yes. Qwen 3.6 Max Preview's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.

What are the best alternatives to Qwen 3.6 Max Preview?

If Qwen 3.6 Max Preview doesn't fit, consider Trinity Mini, Trinity Large Thinking, Trinity Large Preview. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

最近更新:

Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.