TL;DR: Qwen3-VL — the most powerful vision-language model in the Qwen series — is now available on SiliconFlow. This release delivers breakthrough upgrades: superior text understanding & generation, multimodal reasoning, advanced spatial & video perception, 262K context windows, OCR across 32 languages, and stronger agent interaction. Powered by Dense & MoE architectures up to 235B parameters with innovations like Interleaved-MRoPE and DeepStack, it sets a new benchmark for multimodal AI.
Now, both Instruct and Thinking variants are live on SiliconFlow. Start building with SiliconFlow's production-ready API today!
We're excited to announce that Qwen3-VL series is now live on SiliconFlow. As the next-generation vision-language model built to better see, understand, and respond to the world, Qwen3-VL delivers breakthrough capabilities that redefine multimodal AI. It enables precise video understanding, expanded OCR across 32 languages with improved handling of rare characters and historical texts, and 262K context window for ultra-long content analysis.
SiliconFlow now offers both Instruct and Thinking editions: the former optimized for efficient execution, and the latter enhanced for deeper reasoning—giving users the flexibility to choose the right model for their needs.
Through SiliconFlow's Qwen3-VL API, you can expect:
Cost-effective Pricing:
Qwen3-VL-30B-A3B-Instruct $0.29/M tokens (input) and $1/M tokens (output)
Qwen3-VL-30B-A3B-Thinking $0.29/M tokens (input) and $1/M tokens (output)
Qwen3-VL-235B-A22B-Instruct $0.3/M tokens (input) and $1.5/M tokens (output)
Qwen3-VL-235B-A22B-Thinking $0.45/M tokens (input) and $3.5/M tokens (output)
262K Context Window: Enables seamless processing of lengthy documents and multi-turn conversations.
With these combinations—30B vs 235B, Instruct vs Thinking—SiliconFlow enables developers to select the balance between efficiency, depth, and cost, bringing flexible multimodal intelligence to production at every scale.
Why Qwen3-VL Matters
Most vision-language models face a tradeoff: broad capability or deep reasoning, but rarely both. General models struggle with complex logic, specialized models lack versatility. Seeing isn't understanding—and understanding doesn't guarantee problem-solving.
Qwen3-VL addresses this with a dual-edition approach:
Instruct: Optimized for broad, everyday vision-language tasks with reliable performance.
Thinking: Enhanced with advanced reasoning capabilities for complex problem-solving in STEM and math.
Together, they unlock capabilities in three key areas:
1. Agentic
Visual Agent: Let AI navigate apps and websites for you! It recognizes UI elements, understands their functions, and executes multi-step tasks autonomously. It also achieves top global performance on benchmarks like OS World, and using tools significantly improves its performance on fine-grained perception tasks.
Much Better Spatial Understanding: 2D grounding from absolute coordinates to relative coordinates. It can judge object positions, viewpoint changes, and occlusion relationships. It also supports 3D grounding, laying the foundation for complex spatial reasoning and embodied AI applications.
Design-to-Code: Upload a screenshot or video, and generate production-ready Draw.io diagrams, HTML, CSS, or JavaScript — making “what you see is what you get” visual programming a reality.
2. Perception & Comprehension
Long Context & Long Video Understanding: All models natively support 262K context window, expandable up to 1 million tokens. This means you can input hundreds of pages of technical documents, entire textbooks, and even hours-long videos — and the model will remember everything and retrieve details accurately.
Expanded OCR: Support for 32 languages, robust performance with blurry/tilted/low-light images, better handling of rare characters, ancient texts, and technical jargon, plus improved structure parsing for long documents.
Upgraded Visual Perception & Recognition: By improving the quality and diversity of pre-training data, the model can now recognize a much wider range of objects — from celebrities, anime characters, products, and landmarks, to animals and plants — covering both everyday life and professional “recognize anything” needs.
3. Math & Language
Stronger Multimodal Reasoning (Thinking Version): The Thinking model is specially optimized for STEM and math reasoning. When facing complex subject questions, it can notice fine details, break down problems step by step, analyze cause and effect, and give logical, evidence-based answers. It achieves strong performance on reasoning benchmarks like MathVision, MMMU, and MathVista.
Superior Text-Centric Performance: Qwen3-VL employs early-stage joint pretraining of text and visual modalities, continuously strengthening its language capabilities. Its performance on text-based tasks matches that of Qwen3-235B-A22B-2507 — the flagship language model — making it a truly “text-grounded, multimodal powerhouse” for the next generation of vision-language models.
Benchmark Performance & Technical Architecture Updates
Qwen3-VL not only demonstrates broad vision-language skills but also delivers state-of-the-art performance across multimodal and pure text evaluations.
Qwen3-VL-235B-A22B-Instruct & Qwen3-VL-235B-A22B-Thinking:
Beyond the benchmark performance, Qwen3-VL-235B-A22B-Instruct has also achieved remarkable traction in the open-source community. According to OpenRouter's latest statistics (October 2025), it ranks #1 for image processing with a 48% market share, surpassing other leading multimodal models such as Gemini 2.5 Flash and Claude Sonnet 4.5.
Notably, SiliconFlow also serves as a provider on OpenRouter, offering Qwen3-VL-235B-A22B-Instruct alongside other leading models such as DeepSeek-V3.2-Exp, GLM-4.6, Kimi K2-0905, and GPT-OSS-120B, giving developers unified access to a wide range of cutting-edge models.
Qwen3-VL-30B-A3B-Instruct & Qwen3-VL-30B-A3B-Thinking:
Architectural Innovations
Three core breakthroughs power Qwen3-VL's capabilities:
Interleaved-MRoPE: Full‑frequency allocation over time, width, and height via robust positional embeddings, enhancing long‑horizon video reasoning.
DeepStack: Fuses multi‑level ViT features to capture fine‑grained details and sharpen image–text alignment.
Text–Timestamp Alignment: Moves beyond T‑RoPE to precise, timestamp‑grounded event localization for stronger video temporal modeling.
Real-world Application Scenarios
Video Content Analysis & Indexing Process hours of video with frame-accurate understanding—ask "What happened at minute 15?" or "Summarize key topics discussed by the speaker in red." Ideal for media companies, educational platforms, and content moderation needing efficient long-form analysis.
Intelligent Document Processing Extract structured information from complex documents in 32 languages—including historical archives, technical manuals, and blurry scans. Handle entire books (up to 1M tokens) for legal research, academic analysis, or enterprise knowledge management.
No-Code Development & UI Automation Upload design mockups to generate production-ready code, or let Visual Agent navigate apps autonomously—filling forms, testing workflows, and executing multi-step tasks. Accelerate prototyping, QA automation, and reduce manual coding time.
STEM Education & Research Analyze scientific diagrams and mathematical equations with step-by-step reasoning. The Thinking edition breaks down complex problems, explains causality, and provides evidence-based answers for students, researchers, and educators.
Get Started Immediately
1. Explore: Try Qwen3-VL series in the SiliconFlow playground.
2. Integrate: Use our OpenAI-compatible API. Explore the full API specifications in the SiliconFlow API documentation.
Whether you're building multimodal agents, automating UI workflows, or analyzing hours of video, Qwen3-VL gives you the power to see, understand, and reason.
Get started instantly with SiliconFlow's production-ready API and bring visual intelligence into your workflow today!
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