Zamba2-VL is a family of 1.2B–7B hybrid Mamba2-transformer vision-language models that match leading transformer VLMs on image, reasoning, OCR, grounding and counting benchmarks while delivering roughly 10x lower time-to-first-token.
Cobra: Extending 10 mamba to multi-modal large language model for efficient inference.arXiv preprint arXiv:2403.14520, 2024
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The paper consolidates existing research on Mamba models, their architecture variants, adaptations to different data modalities, and applications across domains.
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Zamba2-VL Technical Report
Zamba2-VL is a family of 1.2B–7B hybrid Mamba2-transformer vision-language models that match leading transformer VLMs on image, reasoning, OCR, grounding and counting benchmarks while delivering roughly 10x lower time-to-first-token.