Jonathan writes for THE DECODER about how AI tools can improve both work and creative projects.
Content Summary
A few months after launching Qwen3-VL, Alibaba has released a detailed technical report on the open multimodal model. The data shows the system excels at image-based math tasks and can analyze hours of video footage.
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The system handles massive data loads, processing two-hour videos or hundreds of document pages within a 256,000-token context window.
In "needle-in-a-haystack" tests, the flagship 235-billion-parameter model located individual frames in 30-minute videos with 100 percent accuracy. Even in two-hour videos containing roughly one million tokens, accuracy held at 99.5 percent. The test works by inserting a semantically important "needle" frame at random positions in long videos, which the system must then find and analyze.
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In published benchmarks, the Qwen3-VL-235B-A22B model often beats Gemini 2.5 Pro, OpenAI GPT-5, and Claude Opus 4.1 - even when competitors use reasoning features or high thinking budgets. The model dominates visual math tasks, scoring 85.8 percent on MathVista compared to GPT-5's 81.3 percent. On MathVision, it leads with 74.6 percent, ahead of Gemini 2.5 Pro (73.3 percent) and GPT-5 (65.8 percent).
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