{"slug": "introducing-ryzova-alphi-v1-gemma-4-based-multimodal-ai-model-with-fp16-gguf", "title": "Introducing Ryzova Alphi v1 — Gemma 4-Based Multimodal AI Model with FP16 & GGUF", "summary": "Ryzova released Ryzova Alphi v1, a multimodal AI model built on Google Gemma 4 E2B-it, publishing FP16 Safetensors weights and F16, Q4_K_M, Q6_K and Q8_0 GGUF variants on Hugging Face with a research archive DOI. Ryzova said initial inference and compatibility diagnostics via llama.cpp, the LM-Evaluation Harness and ARC-Easy and IFEval samples completed successfully, but full standardized benchmark scores are not yet available and the company is making no comparative performance claims. The model targets English and Sinhala, and Ryzova said its Matrix Memory, Growing Brain, knowledge retrieval and agent tools components are broader research work not verified or packaged within the downloadable GGUF weights.", "body_md": "Hello Hugging Face community!\n\nWe are introducing **Ryzova Alphi v1**, a publicly available AI model release from Ryzova, developed using **Google Gemma 4 E2B-it** as its foundation.\n\nAlphi is part of Ryzova’s broader research into local-first AI, structured memory, adaptive intelligence, and agent-based systems.\n\nThe Hugging Face repository includes:\n\n**FP16 Safetensors** model weights\n\n**F16 GGUF** for full-precision local inference\n\n**Q4_K_M, Q6_K, and Q8_0 GGUF** variants for different hardware requirements\n\nGemma 4 multimodal architecture\n\nEnglish and Sinhala as target languages\n\n**Model repository:** [RyzovaTech/Alphi-v1 · Hugging Face](https://huggingface.co/RyzovaTech/Alphi-v1)\n\n**Research archive DOI:** [RyzovaTech/Alphi-v1 · Hugging Face](https://doi.org/10.57967/hf/11373)\n\nBeyond the neural model release, Ryzova is investigating several system-level capabilities:\n\n**Matrix Memory:** Structured and persistent memory systems\n\n**Growing Brain:** Reusable knowledge and capability development\n\n**Knowledge retrieval:** Retrieval-augmented information access\n\n**Agent tools:** Controlled tool execution and multi-step workflows\n\nThese are broader Ryzova runtime and research components. They should not be interpreted as capabilities independently verified or fully packaged within the downloadable GGUF weights.\n\nWe have completed initial inference and compatibility diagnostics using:\n\nllama.cpp\n\nF16 GGUF inference\n\nLM-Evaluation Harness\n\nARC-Easy and IFEval diagnostic samples\n\nThe initial diagnostic completed successfully. However, **full standardized benchmark scores are not yet available**, and we are not making comparative performance claims at this stage.\n\nWe would appreciate feedback on:\n\nLocal inference compatibility\n\nGemma 4 model evaluation\n\nQuantized inference behavior\n\nReproducible benchmarking\n\nEnglish and Sinhala testing\n\nPotential integration with memory-augmented agents\n\nWe welcome technical discussion, reproducible test results, and constructive feedback.\n\nThank you for exploring Alphi!", "url": "https://wpnews.pro/news/introducing-ryzova-alphi-v1-gemma-4-based-multimodal-ai-model-with-fp16-gguf", "canonical_source": "https://discuss.huggingface.co/t/introducing-ryzova-alphi-v1-gemma-4-based-multimodal-ai-model-with-fp16-gguf/191474#post_1", "published_at": "2026-11-05 17:07:17+00:00", "updated_at": "2026-11-05 17:22:47.377300+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-research", "ai-tools", "ai-agents"], "entities": ["Ryzova", "Ryzova Alphi v1", "Google Gemma 4 E2B-it", "Hugging Face", "llama.cpp", "LM-Evaluation Harness", "ARC-Easy", "IFEval"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/introducing-ryzova-alphi-v1-gemma-4-based-multimodal-ai-model-with-fp16-gguf", "markdown": "https://wpnews.pro/news/introducing-ryzova-alphi-v1-gemma-4-based-multimodal-ai-model-with-fp16-gguf.md", "text": "https://wpnews.pro/news/introducing-ryzova-alphi-v1-gemma-4-based-multimodal-ai-model-with-fp16-gguf.txt", "jsonld": "https://wpnews.pro/news/introducing-ryzova-alphi-v1-gemma-4-based-multimodal-ai-model-with-fp16-gguf.jsonld"}}