vision-language-model

StepFun has released Step-3.7-Flash, a 198B-parameter sparse Mixture-of-Experts vision-language model that activates 11B parameters per token and delivers up to 400 tokens per second. The model supports a 256K context window, three selectable reasoning levels, and is priced at $0.20 per million input tokens (cache miss) and $1.15 per million output tokens.

NVIDIA released LocateAnything-3B, a 3-billion parameter vision-language model that predicts bounding boxes in parallel rather than token-by-token, achieving up to 2.5× higher throughput compared to autoregressive approaches. The model, trained on 12M images with 138M+ queries and 785M bounding boxes, supports object detection, GUI element grounding, and robotics perception.

Liquid AI has released LFM2.5-VL-450M, a refreshed 450M-parameter vision-language model built on an updated LFM2.5-350M backbone. The model features a 32,768-token context window, supports 9 languages, handles native 512×512 pixel images, and adds bounding box prediction and function calling capabilities. Performance improvements span both vision and language benchmarks compared to its predecessor.

IBM announced Granite 4.0 3B Vision, a 3 billion parameter vision-language model designed for enterprise document processing. The model achieves 86.4% on Chart2Summary and 92.1% TEDS score on cropped table extraction, shipped as a LoRA adapter on Granite 4.0 Micro to enable modular text-only fallbacks.