c0mp1eX/gemma-4-31B-it

VISIONConcurrent Unit Cost:2Model Size:31BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 9, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The c0mp1eX/gemma-4-31B-it model is a 30.7 billion parameter instruction-tuned multimodal large language model developed by Google DeepMind. Part of the Gemma 4 family, it handles text and image inputs with a 256K token context window. This model is optimized for advanced reasoning, coding, and agentic capabilities, featuring native system prompt support and enhanced multimodal understanding.

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Overview

c0mp1eX/gemma-4-31B-it is a 30.7 billion parameter instruction-tuned model from Google DeepMind's Gemma 4 family. It is a dense model designed for frontier-level performance on consumer GPUs and workstations, featuring a 256K token context window. This model is multimodal, processing text and image inputs, and is built with a hybrid attention mechanism for efficient long-context processing. It introduces configurable thinking modes for enhanced reasoning and native function-calling support for agentic workflows.

Key Capabilities

  • Multimodal Understanding: Processes text and images, with variable aspect ratio and resolution support. Video analysis is also supported by processing sequences of frames.
  • Advanced Reasoning: Features a built-in reasoning mode that allows the model to think step-by-step.
  • Long Context: Supports a substantial 256K token context window.
  • Enhanced Coding: Demonstrates notable improvements in coding benchmarks and offers code generation, completion, and correction.
  • Agentic Workflows: Includes native function-calling support for structured tool use.
  • Multilingual Support: Pre-trained on over 140 languages with out-of-the-box support for 35+ languages.

Good For

  • Content Creation: Generating creative text formats, marketing copy, and email drafts.
  • Conversational AI: Powering chatbots, virtual assistants, and interactive applications.
  • Research & Education: Serving as a foundation for VLM and NLP research, and supporting language learning tools.
  • Image Data Extraction: Interpreting and summarizing visual data for text communications, including OCR and document parsing.
  • Complex Reasoning Tasks: Leveraging its thinking mode for tasks requiring structured problem-solving.

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