Qwen3 VL 30B A3B
Alibaba's open-weights vision-language model with tool use, web search, and private TEE inference on Venice.
Overview
What is Qwen3 VL 30B A3B
Qwen3 VL 30B A3B is an open-weights vision-language model from Alibaba's Qwen team, released in October 2025. It processes images and text together, supports tool use and web search, and offers a 128K context window. The model runs privately on Venice with zero retention and end-to-end encryption.
Running it privately on Venice
On Venice, Qwen3 VL 30B A3B runs inside a TEE with end-to-end encryption and zero retention — your multimodal prompts and images are never stored or used for training. You get permissionless, open-weight sovereignty with vision, tool use, and web search capabilities at a fraction of Big-Tech prices, all without surveillance.
Assessment
Strengths and limitations
- Permissionless access to open weights under Apache 2.0, enabling self-hosting, fine-tuning, and full model sovereignty.
- Native vision-language understanding with tool use, web search, and function calling for agentic workflows.
- Strong OCR across 32 languages and advanced spatial perception for GUI automation and visual coding.
- 128K context window supports long documents and extended image sequences on Venice.
- Extremely cost-efficient compared to closed frontier rivals — multimodal inference without the Big-Tech tax.
- Not uncensored: carries standard safety alignment that may refuse certain prompts.
- Reasoning depth sits below top-tier closed models; best for practical tasks rather than frontier research.
- Context window on Venice is 128K, while the open weights natively support up to 256K (expandable to 1M).
Capabilities
What it supports
- Tool use / function calling
- Vision (image input)
- Reasoning
- Web search
- Code-optimized
- Structured output (JSON schema)
- Audio input
- Video input
- Multiple image inputs
- Log probabilities
Specifications
Datasheet
- Maker
- Alibaba Cloud (Qwen team)
- Released
- October 6, 2025
- Modality
- Vision-language (text + image input, text output)
- Architecture
- Mixture of Experts (MoE)
- Parameters
- 30B total, 3B active
- Open weights
- Yes — Apache 2.0
- Context window
- 128K tokens
- Max output
- 4.096K tokens
- Capabilities
- Vision, Function calling, Web search
- Privacy on Venice
- Private — zero retention
- Available on Venice since
- Mar 2026
API
Call it from your code
Venice exposes an OpenAI-compatible API. Point your base URL at Venice and pass the model id.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "e2ee-qwen3-vl-30b-a3b-p",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Pricing
What it costs on Venice
Billed per token on Venice: $0.25 per 1M input tokens and $0.90 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Alternatives
How it compares
| Model | Context window | Open weights | Price (Venice) | Best for |
|---|---|---|---|---|
| Qwen3 VL 30B A3B | 128K tokens | Yes | $0.25 in · $0.90 out / 1M | Vision + tool use |
| Google Gemma 4 31B Instruct | 256K tokens | Yes | $0.12 in · $0.36 out / 1M | Ultra-long context |
| Kimi K2.6 | 256K tokens | Yes | $0.75 in · $3.50 out / 1M | General reasoning |
| Claude Sonnet 4.6 | 1M tokens | No | $3.60 in · $18 out / 1M | Frontier accuracy |
The only open-weights vision-language model in this group, offering multimodal tool use and web search at the lowest cost.
Use cases
What it is good for
- 01Document AI and OCR pipelines for invoices, forms, and scanned books in 32 languages.
- 02Visual coding and UI automation from screenshots and wireframes.
- 03Multimodal content review and structured data extraction from images.
- 04Agentic workflows that combine web search, tool use, and vision reasoning.
- 05Long-context image and text analysis for research and compliance.
Prompting
Getting better results
Upload high-resolution images for best OCR accuracy and spatial grounding.
Explicitly request tool use or web search when you need live data or external actions.
For long documents, place images near their relevant text to keep context within the 128K window.
FAQ
Frequently asked questions
Qwen3 VL 30B A3B is an open-weights vision-language model from Alibaba's Qwen team, released in October 2025. It accepts images and text, supports tool use and web search, and offers a 128K context window on Venice.
On Venice you pay $0.25 per 1M input tokens and $0.90 per 1M output tokens, with no subscription required.
Yes. It is released under the Apache 2.0 license, so you can download, self-host, and fine-tune the weights. On Venice you get the same open weights with private, zero-retention inference.
Yes. It supports function calling and web search on Venice, letting it invoke external tools and retrieve live information during a conversation.
No. While Venice runs it privately with zero retention and end-to-end encryption, the model itself carries standard safety alignment from its original training.
Claude Sonnet 4.6 leads on raw reasoning and offers a 1M context window, but it is closed and far more expensive. Qwen3 VL 30B A3B is the better choice for open-weights sovereignty, vision tasks, and cost-efficient multimodal workflows.
The model supports long-context image sequences and video understanding natively, but on Venice the context window is 128K tokens. For hours-long video, chunk or sample frames to fit within the limit.
It runs inside a TEE with end-to-end encryption and zero retention — your prompts and images are never stored, profiled, or used for training.
Run Qwen3 VL 30B A3B privately
No prompt logging. No data used for training.