LLMPrivate

Qwen3 VL 235B

Alibaba's 235B-parameter open-weights vision-language MoE with tool use, web search, and visual agent capabilities.

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Provider
Alibaba Cloud
Price
$0.21 in · $1.90 out / 1M
Context window
128K tokens
Released
September 22, 2025
License
Apache 2.0

What is Qwen3 VL 235B?

Qwen3 VL 235B is Alibaba Cloud's open-weights vision-language model built on a Mixture-of-Experts architecture. It processes text, images, and video, supports tool use and web search, and offers strong spatial reasoning and visual coding capabilities. The 235B-parameter MoE runs with 22B active parameters and is licensed under Apache 2.0.

Use it privately on Venice

On Venice, Qwen3 VL 235B runs under a private, zero-retention privacy tier — your prompts and images are not stored, profiled, or used for training. You get native vision, tool use, web search, and structured JSON output on an open-weights Apache 2.0 model, with no Big-Tech surveillance or account-linked history.

Private (zero retention)
No prompt training
TEE · hardware enclave
End-to-end encrypted

What can it do?

Strengths
  • Open-weight Apache 2.0 vision-language model with native tool use, web search, structured JSON output, and multiple-image support.
  • Strong visual reasoning and spatial perception, including GUI agent operation, visual coding from screenshots, and advanced OCR across 32 languages.
  • Efficient MoE inference235B total parameters with 22B active per forward pass, delivering high-end multimodal quality without dense-model compute costs.
  • Handles interleaved text-image-video contexts for complex document analysis and video indexing workflows.
Limitations
  • The Instruct variant prioritizes speed and cost over maximum reasoning depth; for complex STEM or causal analysis the Thinking edition may perform better.
  • On Venice it is quantized to fp8 and served at a 128K context window, which may limit very long-document or hour-long video tasks compared to the native 256K–1M range cited in upstream docs.
  • While open weights, it is not uncensored — standard safety alignment is still present.
  • Vision-language latency is higher than text-only models, and output costs are nearly $2 per million tokens, so high-volume text-only workloads may be cheaper on DeepSeek V3.2 or Gemma 4.

Qwen3 VL 235B capabilities

How to use it via API

Venice exposes an OpenAI-compatible API. Swap your base URL and call qwen3-vl-235b-a22b.

curl https://api.venice.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3-vl-235b-a22b",
    "messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
  }'

Specifications

MakerAlibaba Cloud (Qwen team)
ReleasedSeptember 2025
ArchitectureMixture of Experts (MoE)
Parameters235B total, 22B active
Open weightsYes — Apache 2.0
Context window128K tokens
Max output16.384K tokens
CapabilitiesVision, Function calling, Web search
Privacy on VenicePrivate — zero retention
Available on Venice sinceJan 2026

Pricing

Billed per token on Venice: $0.21 per 1M input tokens and $1.90 per 1M output tokens.

Input / 1M tokens
$0.21
Output / 1M tokens
$1.90
Cached input / 1M
$0.10

New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.

Qwen3 VL 235B vs alternatives

ModelContext windowOpen weightsPrice (Venice)Best for
Qwen3 VL 235B128K tokensYes$0.21 in · $1.90 out / 1MVision, tool use & web search
DeepSeek V3.2160K tokensYes$0.33 in · $0.48 out / 1MText reasoning & coding
Kimi K2.6256K tokensYes$0.75 in · $3.50 out / 1MLong-context text
Claude Sonnet 4.61M tokensNo$3.60 in · $18 out / 1MGeneral multimodal

The only open-weights vision model in this set with native tool use, web search, and multiple-image support at under $2/1M output.

What is it good for?

  • Visual document analysis and OCR for invoices, forms, and long scans in 32 languages.
  • GUI automation and visual agent tasks on desktop or mobile interfaces.
  • Front-end coding from design mockups: generating HTML, CSS, or JS from screenshots.
  • Multimodal data extraction and structured cataloging from product images or video frames.
  • Grounded research with web search over current visual content and news.

Prompting tips

  • Use interleaved image-text prompts for document analysis; place the image first, then ask specific questions about regions or text.
  • For visual coding, explicitly state the desired output format (e.g., 'Generate HTML/CSS from this screenshot').
  • Leverage tool use and web search when you need real-time facts to interpret images or verify visual claims.
  • Upload multiple images in one conversation to compare products, track changes across frames, or assemble a visual narrative.

Version history

Qwen3-VL-235B-A22B-Instruct
2025-09

Standard instruction-tuned variant with vision, tool use, and web search.

Qwen3-VL-235B-A22B-Thinking
2025-09

CurrentReasoning-enhanced edition for deeper multimodal reasoning and STEM tasks.

Frequently asked questions

Qwen3 VL 235B is Alibaba Cloud's open-weights vision-language model released in September 2025. Built on a Mixture-of-Experts architecture with 235B total and 22B active parameters, it understands text, images, and video, supports tool use and web search, and excels at visual reasoning, OCR, and GUI automation.

Venice charges $0.21 per 1M input tokens and $1.90 per 1M output tokens. Cached input is $0.10 per 1M. There is no subscription; you pay only for the tokens you use.

Yes. The weights are released under the Apache 2.0 license by the Qwen team, permitting commercial use and self-hosting. On Venice it runs as open weights with fp8 quantization.

New Venice accounts include free credits to try the model, with no credit card required. Beyond the free tier, usage is billed per token at the published rates.

Yes. On Venice it supports function calling, structured JSON output, web search, and multiple image inputs, making it suitable for agent workflows and automated visual tasks.

Choose Qwen3 VL 235B for image, video, and multimodal document tasks; it offers vision and visual agent capabilities that DeepSeek V3.2 does not. Choose DeepSeek V3.2 for pure text reasoning and coding at lower cost if you do not need vision.

It can describe, analyze, and reason over images; perform OCR in 32 languages; generate code from UI screenshots; judge spatial relationships and occlusions; and process multiple images in a single conversation.

Yes. On Venice the model has web search capability, so it can ground answers in current information beyond its training cutoff.

Related models

Run Qwen3 VL 235B privately.

No prompt logging. No data used for training. Free to start — no credit card.

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