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Gemma is a family of open-weight language models released by Google for text generation and related NLP tasks.
The Gemma 4 family of open-weights models from Google includes four variants, spanning a range of sizes from 2B effective parameters to 31B parameters and including both Mixture of Experts (MoE) and dense architectures. These multimodal models ingest text, vision, and for select variants, audio inputs and generate text outputs. They support context sizes of up to 256K tokens, and have been trained for thinking, coding, function calling, optical character recognition (OCR), object recognition and automatic speech recognition tasks. For relatively compact models they have outstanding language s
Day 0 Support for Gemma 4 on AMD Processors and GPUs… GPU deployment with Lemonade and ROCm To run Gemma 4 on AMD GPUs with ROCm acceleration: Install Lemonade and download the preview ROCm build of llama.cpp for your GPU architecture from the release artifacts e.g., llama-windows-rocm-gfx1151-x64 for Radeon™ 8060S . …
… Figure 2 PACE/vLLM Speedup demonstrates these gains across input lengths 128, 1920 , output lengths 128, 1920 , and batch sizes 1, 32, 128 over a diverse set of models spanning multiple architectures and scales : Phi-4, OPT-6.7B, Llama-3.1-8B, Llama-3.2-3B, Qwen2-7B, Gemma-3-4B, and Gemma-3-12B . …
… Our accelerated update cadence, with biweekly major releases and day-zero support for emerging models, helps ensure enterprises stay ahead in a fast-moving AI landscape. …
… AMD’s Day-0 enablement of leading open and frontier models for example Qwen3.6, Gemma 4, Xiaomi MiMo-V2.5-Pro, and Baidu Ernie Image means OpenMAIC can adopt new generators on AMD ROCm as soon as they ship. …