Revolutionizing On-Device Utility with E2B and E4B Models
At the forefront of technological innovation, the E2B and E4B models are reshaping the landscape of on-device utility. Diverging from the traditional emphasis on raw parameter count, these models prioritize multimodal capabilities, low-latency processing, and seamless ecosystem integration. This strategic approach ensures they deliver unparalleled performance and versatility across various applications.
Powerful, Accessible, Open
To empower the next generation of groundbreaking research and products, the Gemma 4 models have been meticulously sized for optimal efficiency. They are fine-tuned to operate effectively across diverse hardware platforms, from the billions of Android devices worldwide to laptop GPUs and developer workstations. This versatility ensures that researchers and developers can leverage state-of-the-art performance tailored to their specific tasks.
The success of this approach is already evident. Collaborations with institutions like INSAIT have led to the development of BgGPT, a pioneering model for the Bulgarian language. Additionally, joint efforts with Yale University on the Cell2Sentence Scale are uncovering new avenues for cancer therapy.
Gemma 4 represents our most powerful open model family to date:
- Advanced Thinking: With capabilities for multi-level planning and deep logic, Gemma 4 excels in mathematics and instruction-following benchmarks.
- Agentic Workflows: Native function call support and structured JSON output enable the creation of autonomous agents adept at interacting with various tools and APIs.
- Code Generation: Transform your workstation into a local AI code assistant with Gemma 4’s support for high-quality offline code.
- Vision and Audio: Models natively process video and images, supporting variable resolutions and excelling at visual tasks like OCR. The E2B and E4B models also offer native audio input for speech recognition.
- Longer Context: With a 128KB context window for Edge models and up to 256KB for larger models, processing long content seamlessly is a reality.
- Over 140 Languages: Trained in over 140 languages, Gemma 4 facilitates the creation of inclusive, high-performance applications for a global audience.
Versatile Models for Diverse Hardware
To ensure premium reasoning capabilities are available wherever needed, the Gemma 4 model weights are released in sizes tailored to specific hardware and use cases.
Models 26B and 31B: Frontier Intelligence, Offline on Your PCs
Our unquantized bfloat16 weights are optimized for researchers and developers seeking state-of-the-art reasoning on accessible hardware. These weights fit efficiently on a single 80GB NVIDIA H100 GPU. For local setups, quantized versions run natively on consumer GPUs, supporting IDEs, coding wizards, and agent workflows. The 26B Mixture of Experts (MoE) model prioritizes latency, activating only 3.8 billion of its parameters during inference for fast token generation. Meanwhile, the 31B Dense model maximizes raw quality, providing a robust foundation for fine-tuning.
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