HPT

HyperGAI's HPT is an open-source family of multimodal large language models that process text, images, and video without needing a cloud API. Built for developers and researchers, HPT lets you embed vision-language capabilities directly into your own applications—whether on a phone, an IoT device, or a server. The lineup includes HPT 1.5 Edge, a ~4B model optimized for edge and mobile, and HPT 1.5 Air, an 8B model built on a Llama 3 backbone for server-side tasks. Both are freely downloadable from Hugging Face and GitHub under a permissive license, and both deliver strong performance on benchmarks for visual question answering, document understanding, chart reading, and code generation from visual inputs. HyperGAI positions HPT as a bridge between open-source and proprietary multimodal models. In head-to-head comparisons, the 8B Air model has been shown to outperform bigger proprietary systems in some cases, while the 4B Edge model brings near-state-of-the-art performance to constrained environments. The company is also researching multimodal diffusion models for image and video generation, signaling a broader roadmap beyond understanding alone. The practical appeal is clear: state-of-the-art multimodal AI that runs locally, giving you privacy, low latency, and no per-token fees. That's a compelling fit for developers embedding vision-language features into mobile apps, edge devices, or privacy-sensitive enterprise workflows. Researchers will also appreciate the open weights and the chance to fine-tune for specialized domains. However, HyperGAI is not a SaaS company—there's no hosted endpoint, no managed UI, and no support team. This is a toolkit for people who can pull a model down and wire it into their own stack. If that describes you, HPT is worth serious consideration; if you want plug-and-play, look elsewhere.