AI 模型情報

Qwen/Qwen3-VL-8B-Instruct

alibaba/qwen3-vl-8b-instruct

出品方: Alibaba (Qwen) · 系列: qwen · 發布 2025-10-15

$0.100
輸入 / 1M token
$0.100
輸出 / 1M token
262K
上下文長度
262K
最大輸出

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

能力清單

工具呼叫推理結構化輸出附件開放權重溫度可調
支援模態: 輸入 text, image · 輸出 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.

Coding73
  • Tool calling40/40
  • Structured output20/20
  • Reasoning0/10
  • Context window (100K → 1M)8/20
  • Provider availability5/10
Agents80
  • Tool calling35/35
  • Structured output25/25
  • Reasoning0/15
  • Output token limit15/15
  • Provider availability5/10
JSON / structured output100
  • Structured output / JSON mode50/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume20/20
Cost efficiency79
  • Headline price (log-scaled)79/95
  • Has prompt-cache pricing0/5
Long context61
  • Context window (100K → 2M)51/90
  • Has published price for full window10/10
Vision86
  • Accepts image input50/50
  • Context window (10K → 1M)21/30
  • Has published price10/10
  • Provider availability5/10
Production-readiness79
  • Number of independent providers25/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers4/10
  • Official model (not derivative)15/15

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
$0.55
< $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
$1.10
< $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
$0.25
< $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
$0.90
< $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
$1.26
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

定價詳情

推薦定價來自 llmgateway · qwen3-vl-8b-instruct

$0.100
輸入
$0.100
輸出

於 5 家供應商可用

服務商服務商模型 ID輸入 / 1M輸出 / 1M上下文發布日期
SiliconFlow (China)
siliconflow-cn
Qwen/Qwen3-VL-8B-Instruct$0.180$0.680262K2025-10-15
NovitaAI
novita-ai
qwen/qwen3-vl-8b-instruct$0.080$0.500131K2025-10-17
Kilo Gateway
kilo
qwen/qwen3-vl-8b-instruct$0.080$0.500131K2025-10-15
SiliconFlow
siliconflow
Qwen/Qwen3-VL-8B-Instruct$0.180$0.680262K2025-10-15
LLM Gateway
llmgateway
qwen3-vl-8b-instruct$0.100$0.100131K2025-08-19

各渠道資料存在不一致

  • context_window varies: 131072, 262000
  • release_date varies (span 59d): 2025-08-19, 2025-10-15, 2025-10-17
  • modalities varies across offerings

各服務商對此模型的回報值不一致。上方「核心數據」採用代表性服務商的值;逐項請以下表為準。

Frequently asked questions

How much does Qwen/Qwen3-VL-8B-Instruct cost?

Qwen/Qwen3-VL-8B-Instruct costs $0.100 per 1M input tokens and $0.100 per 1M output tokens, sourced from llmgateway. 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-8B-Instruct?

Qwen/Qwen3-VL-8B-Instruct 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-8B-Instruct support tool calling?

Yes. Qwen/Qwen3-VL-8B-Instruct 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-8B-Instruct support structured output / JSON mode?

Yes. Qwen/Qwen3-VL-8B-Instruct 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-8B-Instruct accept image input?

Yes. Qwen/Qwen3-VL-8B-Instruct accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check Alibaba (Qwen)'s docs for the exact rule.

Is Qwen/Qwen3-VL-8B-Instruct open-weight?

No. Qwen/Qwen3-VL-8B-Instruct is a proprietary model — only Alibaba (Qwen) (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-8B-Instruct?

If Qwen/Qwen3-VL-8B-Instruct doesn't fit, consider Qwen3.5 397B-A17B, Qwen3 32B, Qwen3 235B A22B Instruct 2507. 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.