Simplismart/gemma-4-31B-it-sharded

VISIONConcurrency Cost:2Model Size:31BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:May 28, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The Gemma 4 31B-it is a 30.7 billion parameter instruction-tuned multimodal language model developed by Google DeepMind. It handles text and image input, generating text output, and features a 256K token context window. This model excels in reasoning, coding, and agentic capabilities, making it suitable for complex text generation and multimodal understanding tasks.

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Gemma 4 31B-it: A Multimodal Powerhouse from Google DeepMind

This model is part of the Gemma 4 family, an advanced series of open multimodal models developed by Google DeepMind. The 31B-it variant is a 30.7 billion parameter instruction-tuned model, capable of processing both text and image inputs to generate text outputs. It boasts a substantial context window of up to 256K tokens and maintains multilingual support across over 140 languages.

Key Capabilities & Advancements

  • Multimodal Understanding: Processes text and images with variable aspect ratio and resolution support. Video analysis is also supported by processing sequences of frames.
  • Enhanced Reasoning: Designed with configurable thinking modes, allowing the model to perform step-by-step reasoning.
  • Coding & Agentic Workflows: Achieves significant improvements in coding benchmarks and includes native function-calling support for building autonomous agents.
  • Long Context: Features a 256K token context window, enabling deep awareness for complex, long-context tasks.
  • Native System Prompt Support: Introduces native support for the system role, facilitating more structured and controllable conversations.

Good For

  • Complex Text Generation: Ideal for tasks requiring advanced reasoning and detailed text output.
  • Multimodal Applications: Excellent for scenarios involving interleaved text and image inputs, such as image captioning, document parsing, and visual question answering.
  • Code Generation & Assistance: Highly capable in generating, completing, and correcting code across various programming languages.
  • Agentic Workflows: Suitable for developing sophisticated AI agents that require structured tool use and function calling.
  • Research & Development: Serves as a robust foundation for researchers exploring advanced VLM and NLP techniques.