unsloth/gemma-3-12b-pt
Hugging Face
VISIONConcurrency Cost:1Model Size:12BQuant:FP8Ctx Length:32kPublished:Mar 12, 2025License:gemmaArchitecture:Transformer0.0K Warm

Gemma 3 (12B) is a 12 billion parameter multimodal language model from Google, built on the same research as Gemini models. It handles both text and image inputs, generating text outputs, and features a large 128K token context window with multilingual support across 140+ languages. This model is optimized for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning, and is suitable for deployment in resource-limited environments.

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Gemma 3 (12B) Overview

This model is a 12 billion parameter variant of the Gemma 3 family, developed by Google DeepMind. It is a multimodal model capable of processing both text and image inputs to generate text outputs. Key features include a substantial 128K token context window and support for over 140 languages, making it versatile for global applications.

Key Capabilities

  • Multimodal Processing: Accepts text and images (normalized to 896x896 resolution) as input.
  • Extensive Context: Utilizes a 128K token context window for comprehensive understanding.
  • Multilingual Support: Trained on data in over 140 languages.
  • Diverse Task Performance: Excels in text generation, image understanding, question answering, summarization, and reasoning.
  • Efficient Deployment: Designed for deployment in environments with limited resources, such as laptops or cloud infrastructure.

Benchmark Highlights (Gemma 3 PT 12B)

  • Reasoning: Achieves 84.2 on HellaSwag (10-shot) and 72.6 on BIG-Bench Hard (few-shot).
  • STEM & Code: Scores 74.5 on MMLU (5-shot) and 71.0 on GSM8K (8-shot).
  • Multilingual: Reaches 64.3 on MGSM and 69.4 on Global-MMLU-Lite.
  • Multimodal: Attains 82.3 on DocVQA (val) and 71.2 on VQAv2.

Good For

  • Content Creation: Generating creative text formats, marketing copy, and email drafts.
  • Conversational AI: Powering chatbots and virtual assistants.
  • Research & Education: Serving as a foundation for VLM/NLP research and language learning tools.
  • Image Analysis: Extracting and interpreting visual data for text communications.
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