Qwen3-VL: The next leap in vision-language AI

Kari Jaaskelainen

27 Nov 2025 — 1 min read

Meet Qwen3-VL, the newest model in the Qwen series that natively understands text, images, and video—at the same time.

Long memory: up to 256K tokens (book-length) with interleaved text+media.
Flexible sizes: 2B/4B/8B/32B dense and 30B-A3B/235B-A22B MoE to balance speed and quality.
Stronger language skills than many text-only LLMs, plus top scores on MMMU, MathVista, and MathVision.
Better spatial-temporal modeling via enhanced interleaved-MRoPE.
DeepStack fuses multi-level vision features for tighter image-language alignment.
Text-based timestamp alignment yields more precise video understanding.

What this means: assistants that keep track across long documents and multi-scene videos, solve visual math step-by-step, and even write code from diagrams—without blowing past typical token or latency budgets.

Paper: https://arxiv.org/abs/2511.21631v1

Paper: https://arxiv.org/abs/2511.21631v1

Register: https://www.AiFeta.com

#AI #Multimodal #VisionLanguage #LLM #MachineLearning #ComputerVision #Qwen #Research

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