Google has rolled out Gemma 4, a collection of open-source artificial intelligence models provided under an Apache 2.0 license. According to the company, developers have downloaded Gemma models more than 400 million times since the initial Gemma release, and those downloads have produced in excess of 100,000 model variants.
The Gemma 4 lineup comprises four configurations: Effective 2B, Effective 4B, a 26B Mixture of Experts (MoE) model, and a 31B Dense model. Google said the 31B iteration currently ranks third among open models on the Arena AI text leaderboard, while the 26B model sits at sixth. The company also stated these models are derived from the same research and technology base as Gemini 3.
Google described the Gemma 4 family as capable of advanced reasoning and agentic workflows, including function-calling and structured JSON output. The models support code generation and can natively process video, images and audio. Context window sizes vary by model class - edge-oriented models offer a 128K token context window, while the larger variants provide up to a 256K context window. Training data covers more than 140 languages, per Google.
On resource requirements, Google said the unquantized bfloat16 weights for both the 26B and 31B models will fit on a single 80GB NVIDIA H100 GPU. By contrast, the Effective 2B and Effective 4B were developed to operate on mobile and Internet of Things hardware, with offline capability on devices including phones, Raspberry Pi boards and the NVIDIA Jetson Orin Nano. Google noted collaboration on the edge models with its Pixel hardware team, Qualcomm Technologies and MediaTek.
For distribution and developer access, Gemma 4 is available through Google AI Studio, Google AI Edge Gallery and Android Studio. Google said there is day-one support across multiple third-party platforms and runtimes, including Hugging Face, vLLM, llama.cpp, MLX, Ollama and NVIDIA NIM. Model weights can be downloaded from Hugging Face, Kaggle or Ollama, and deployment options include Vertex AI, Cloud Run, Google Kubernetes Engine and Google Cloud’s TPU-accelerated serving.
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