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Qwen/Qwen3-VL-32B-Thinking

siliconflow/qwen3-vl-32b-thinking

من siliconflow · العائلة: qwen · أُصدِر 2025-10-21

⚠ هذا نموذج مُحسَّن من المجتمع أو مشتق — وليس إصدارًا رسميًا من المزود.

$0.200
الإدخال / 1M رمز
$1.50
الإخراج / 1M رمز
262K
نافذة السياق
262K
أقصى إخراج

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

القدرات

✓ استدعاء الأدوات✓ تفكير✓ إخراج منظم✓ المرفقات✗ أوزان مفتوحة✓ التحكم بالحرارة
الوسائط المدعومة: إدخال text, image · إخراج 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.

Coding79
  • Tool calling40/40
  • Structured output20/20
  • Reasoning10/10
  • Context window (100K → 1M)8/20
  • Provider availability1/10
Agents91
  • Tool calling35/35
  • Structured output25/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability1/10
JSON / structured output97
  • Structured output / JSON mode50/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume17/20
Cost efficiency57
  • Headline price (log-scaled)57/95
  • Has prompt-cache pricing0/5
Long context61
  • Context window (100K → 2M)51/90
  • 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
$1.75
< $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
$3.50
< $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
$1.15
< $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
$3.10
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$3.30
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

تفاصيل التسعير

السعر المُوصى به من siliconflow · Qwen/Qwen3-VL-32B-Thinking

$0.200
إدخال
$1.50
إخراج

متاح لدى 1 مزود

المزودمعرف نموذج المزودإدخال / 1Mإخراج / 1Mالسياقتاريخ الإصدار
SiliconFlow
siliconflow
Qwen/Qwen3-VL-32B-Thinking$0.200$1.50262K2025-10-21

Frequently asked questions

How much does Qwen/Qwen3-VL-32B-Thinking cost?

Qwen/Qwen3-VL-32B-Thinking costs $0.200 per 1M input tokens and $1.50 per 1M output tokens, sourced from siliconflow. 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/Qwen3-VL-32B-Thinking?

Qwen/Qwen3-VL-32B-Thinking has a context window of 262K tokens, with a max output of 262K tokens per reply. This is the total combined size of prompt + completion.

Does Qwen/Qwen3-VL-32B-Thinking support tool calling?

Yes. Qwen/Qwen3-VL-32B-Thinking 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/Qwen3-VL-32B-Thinking support structured output / JSON mode?

Yes. Qwen/Qwen3-VL-32B-Thinking supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Can Qwen/Qwen3-VL-32B-Thinking accept image input?

Yes. Qwen/Qwen3-VL-32B-Thinking accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check siliconflow's docs for the exact rule.

Is Qwen/Qwen3-VL-32B-Thinking open-weight?

No. Qwen/Qwen3-VL-32B-Thinking is a proprietary model — only siliconflow (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.

What are the best alternatives to Qwen/Qwen3-VL-32B-Thinking?

If Qwen/Qwen3-VL-32B-Thinking doesn't fit, consider inclusionAI/Ring-flash-2.0, inclusionAI/Ling-mini-2.0, inclusionAI/Ling-flash-2.0. 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.

Explore more

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Capability lists this model is in

See also

آخر تحديث:

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.