Google Unveils Gemma 2 2B: A Lightweight AI Model Surpassing GPT-3.5 and Mistral 8x7B

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Google has recently introduced its latest AI model, Gemma 2 2B, a compact yet powerful AI that has outperformed larger models like GPT-3.5 and Mistral 8x7B on several key benchmarks. This announcement comes just weeks after the release of the Gemma 2 best-in-class models. The new Gemma 2 2B includes built-in safety features, and Google has also revealed two new tools: ShieldGemma and Gemma Scope.

“With these additions, researchers and developers can now create safer customer experiences, gain unprecedented insights into our models, and confidently deploy powerful AI responsibly, right on the device, unlocking new possibilities for innovation,” Google stated in its official release.

What is Gemma 2 2B?

Gemma 2 2B is a lightweight AI model designed by Google to deliver exceptional performance by learning from larger models through a process called distillation. Despite its compact size, the model has surpassed all GPT-3.5 models on Chatbot Arena, demonstrating impressive conversational AI capabilities. Google claims that the model can efficiently run on various hardware platforms, ranging from edge devices and laptops to robust cloud deployments using Vertex AI and Google Kubernetes Engine (KGE). Additionally, the model is optimized with the NVIDIA TensorRT-LLM library to enhance its speed.

Gemma 2 2B integrates seamlessly with multiple platforms, including Keras, JAX, Hugging Face, NVIDIA NeMo, Ollama, Gemma.cpp, and will soon be available on the MediaPipe platform to streamline development. The model is open and accessible to developers.

How is Gemma 2 2B Different?

With just 2.6 billion parameters, Gemma 2 2B stands out for being trained on a massive dataset of 2 trillion tokens. On Chatbot Arena, the model scored 1130, matching the performance of significantly larger models like GPT-3.5 Turbo and Mistral – 8x7B. Despite its smaller size, Gemma 2 2B is designed to offer competitive performance, making it a versatile and efficient choice for a wide range of AI applications.

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