Zamba2-VL Technical Report
Researchers have introduced Zamba2-VL, a new family of vision-language models that leverage a hybrid architecture combining Mamba2 state-space layers with transformer blocks. These models demonstrate strong performance across various vision and language tasks, rivaling established transformer-based models like Molmo2 and Qwen3-VL. A key advantage of Zamba2-VL is its significantly faster time-to-first-token, making it particularly suitable for on-device and edge deployments. AI
IMPACT Offers faster inference for vision-language tasks, potentially enabling more responsive on-device AI applications.