Qwen: Qwen3 VL 30B A3B Instruct

Public pricingIntelligence 79/100Medium memory視覚ツール利用

Qwen: Qwen3 VL 30B A3B Instruct は マルチモーダル モデルで、視覚言語理解 に向いています。マルチモーダル入力処理、画像理解、131K tokensのコンテキスト、低コストの特性を組み合わせ、image and video understanding で安定した動作を支えます。品質・速度・コスト が重要な場面に合っており、安定した出力、柔軟な導入、拡張性を求めるチームに実用的です。 安定した応答、長い文脈処理、そして試作から本番まで広く使える柔軟さが必要な場面で役立ちます。 安定した応答、長い文脈処理、そして試作から本番まで広く使える柔軟さが必要な場面で役立ちます。 安定した応答、長い文脈処理、そして試作から本番まで広く使える柔軟さが必要な場面で役立ちます。

Input

$0.13/1M

Output

$0.52/1M

Cached

$0.02/1M

Batch

$0.04/1M

Calculate your Qwen3 VL 30B A3B Instruct bill.

Set your workload — see cost at your exact volume.

What would Qwen3 VL 30B A3B Instruct cost you?

Adjust the workload to see your monthly bill.

1,00010,00050,000250,0001M10M

Technical specifications

Qwen3 VL 30B A3B Instruct at a glance.

Memory

131,072

tokens

Max reply

32,768

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

qwen3

Released

Oct 2025

Training cutoff

Apr 2025

Availability

Public pricing

Status

active

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Qwen3 VL 30B A3B Instruct

  • Screenshot analysis, image understanding, or document OCR.
  • Agentic workflows that call tools or APIs.
  • High-volume workloads where unit cost matters.
  • Multimodal pipelines mixing text + images.

When to look elsewhere

  • Very latency-sensitive, real-time apps where every millisecond counts.

Alternatives

Similar models to compare.

FAQ

Qwen3 VL 30B A3B Instruct — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Qwen3 VL 30B A3B Instruct costs roughly $31 per month. Input is $0.13 /1M tokens and output is $0.52 /1M tokens.
Qwen3 VL 30B A3B Instruct has a 131,072-token context window (medium memory — a long report or a codebase file). That means you can fit about 24,576 words of input and history in a single call.
Beyond text generation, Qwen3 VL 30B A3B Instruct supports understanding images, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Qwen3 VL 30B A3B Instruct was released in October 2025, with training data cut off around April 2025.
Models in a similar class include Qwen3 VL 30B A3B Thinking, Qwen VL Plus, Qwen3 VL 8B Thinking. The "Similar models" section below this FAQ links into each.

Still unsure?

Compare Qwen3 VL 30B A3B Instruct against 100+ other models.

Open the full wizard — pick a use case, set your usage, and see side-by-side monthly costs in under a minute.

Open the comparison wizard