 | Today, we release LFM2.5-VL-450M our most capable vision-language model for edge deployment. It processes a 512×512 image in 240ms and it is fast enough to reason about every frame in a 4 FPS video stream. It builds on LFM2-VL-450M with three new capabilities:
Most production vision systems are still multi-stage: a detector, a classifier, heuristic logic on top. This model does it in one pass:
It runs on Jetson Orin, Samsung S25 Ultra, and AMD 395+ Max. Open-weight, available now on Hugging Face, LEAP, and our Playground. HF model checkpoint: https://huggingface.co/LiquidAI/LFM2.5-VL-450M [link] [comments] |
Liquid AI releases LFM2.5-VL-450M - structured visual understanding at 240ms
Reddit r/LocalLLaMA / 4/9/2026
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Key Points
- Liquid AI has released LFM2.5-VL-450M, a vision-language model targeted for edge deployment, with 512×512 image processing in about 240ms and suitability for ~4 FPS video streams.
- The model improves on LFM2-VL-450M by adding bounding box prediction, multilingual visual understanding across 9 languages (reported MMMB score gains), and function-calling support.
- It aims to simplify production vision pipelines by performing object localization, contextual reasoning, and structured output generation in a single on-device pass rather than multi-stage detector/classifier plus heuristics.
- LFM2.5-VL-450M runs on devices including NVIDIA Jetson Orin, Samsung S25 Ultra, and AMD 395+ Max, and is released as open-weight via Hugging Face and Liquid AI’s distribution channels.
- The release provides immediate availability through an HF checkpoint and accompanying blog post, enabling developers to evaluate and integrate structured visual understanding on edge hardware.
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