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// 80d agoMODEL RELEASE
Qwen 3.5 trades DeepStack for native multimodal speed
A Reddit discussion highlights the shift in Qwen 3.5's architecture, specifically the move away from the DeepStack feature-fusion method. The new "native multimodal agent" design prioritizes high throughput and unified reasoning over the complex, multi-level visual stacking of previous versions.
// ANALYSIS
Alibaba's Qwen 3.5 is a major pivot toward efficiency and speed, even if it means ditching some fine-grained visual tricks.
- –DeepStack's removal (or evolution) simplifies the vision-language bottleneck, enabling speeds of over 100 tokens/sec.
- –The shift to Multi-Token Prediction (MTP) effectively replaces the need for separate draft models or stacking layers.
- –Early benchmarks suggest the model is faster and better at reasoning, though some users report "overthinking" issues in specific logic tasks.
- –The tradeoff favors scaling and throughput, making the models more viable for real-time edge deployment.
// TAGS
qwenllmmultimodalvision-languagealibabaarchitecture
DISCOVERED
80d ago
2026-03-08
PUBLISHED
83d ago
2026-03-06
RELEVANCE
8/ 10
AUTHOR
foldl-li