8B open-weight multimodal model trained with GRPO+GDPO. Competitive with Gemini 2.5 Pro on DocVQA and chart understanding. New SOTA for open-weight VLMs on MMMU.
Compact 15B open-weight multimodal reasoning model from Microsoft. Achieves competitive VLM performance with much less compute via careful data curation and dynamic-resolution encoders.
Introduces Gaussian GRPO (G2RPO), replacing standard linear scaling in GRPO with non-linear distributional matching. OpenVLThinkerV2-7B achieves new SOTA for open-source 7B models on MMMU (71.6%), Mat
Proposes RLSD combining self-distillation magnitude with RLVR direction. On Qwen3-VL-8B, achieves best avg accuracy across 5 multimodal reasoning benchmarks, outperforming GRPO by 2.32% on average.
Compact 15B open-weight multimodal reasoning model from Microsoft. Achieves competitive VLM performance with much less compute via careful data curation and dynamic-resolution encoders.
Compact 15B open-weight multimodal reasoning model from Microsoft. Achieves competitive VLM performance with much less compute via careful data curation and dynamic-resolution encoders.
8B open-weight multimodal model trained with GRPO+GDPO. Competitive with Gemini 2.5 Pro on DocVQA and chart understanding. New SOTA for open-weight VLMs on MMMU.
Compact 15B open-weight multimodal reasoning model from Microsoft. Achieves competitive VLM performance with much less compute via careful data curation and dynamic-resolution encoders.
8B open-weight multimodal model trained with GRPO+GDPO. Competitive with Gemini 2.5 Pro on DocVQA and chart understanding. New SOTA for open-weight VLMs on MMMU.
Compact 15B open-weight multimodal reasoning model from Microsoft. Achieves competitive VLM performance with much less compute via careful data curation and dynamic-resolution encoders.