arolstar52/gemma-4-31B-it

VISIONConcurrent Unit Cost:2Model Size:31BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 3, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The arolstar52/gemma-4-31B-it is a 31 billion parameter instruction-tuned multimodal language model developed by Google DeepMind, part of the Gemma 4 family. It supports 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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Model Overview

arolstar52/gemma-4-31B-it is a 31 billion parameter instruction-tuned model from the Gemma 4 family, developed by Google DeepMind. This model is multimodal, capable of processing text and image inputs to generate text outputs. It features a substantial 256K token context window and supports over 140 languages, making it highly versatile for various applications.

Key Capabilities

  • Multimodality: Processes text and image inputs, with the ability to interleave them freely within a single prompt. Video input is supported by processing sequences of frames.
  • Reasoning: Designed with configurable thinking modes for enhanced reasoning capabilities, allowing step-by-step internal processing.
  • Extended Context: Offers a 256K token context window, enabling the handling of long and complex inputs.
  • Coding & Agentic Features: Demonstrates significant improvements in coding benchmarks and includes native function-calling support for building autonomous agents.
  • Native System Prompt Support: Integrates native support for the system role, facilitating more structured and controllable conversations.

Good For

  • Complex Text Generation: Ideal for generating creative text formats, code, and detailed responses requiring deep understanding.
  • Multimodal Understanding: Suited for tasks involving image analysis, document parsing, and visual data extraction.
  • Agentic Workflows: Its function-calling support makes it excellent for developing AI agents that interact with tools and systems.
  • Research and Development: Serves as a robust foundation for researchers exploring advanced VLM and NLP techniques.

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