Jan v2 VL: Multimodal Agent for Long Horizon Tasks Overview Jan v2 VL is an 8B parameter vision–language model for long horizon, multi step tasks in real software environments (e.g., browsers and desktop apps). It combines language reasoning with visual perception to follow complex instructions, maintain intermediate state, and recover from minor execution errors. We recognize the importance of long horizon execution for real world tasks, where small per step gains compound into much longer successful chains—so Jan v2 VL is built for stable, many step execution. For evaluation, we use The Illusion of Diminishing Returns: Measuring Long Horizon Execution in LLMs , which measures execution length. This benchmark aligns with public consensus on what makes a strong coding model—steady, low drift step execution—suggesting that robust long horizon ability closely tracks better user experience. Variants Jan v2 VL low — efficiency oriented, lower latency Jan v2 VL med — balanced latency/quality Jan v2 VL high — deeper reasoning; higher think time Intended Use Tasks where the plan and/or knowledge can be provided up front, and success hinges on stable, many step execution with minimal drift…
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