mrMEtr/functiongemma-270m-it-mobile-actions

TEXT GENERATIONPricing:Input $0.04 / Cached $0.008 / Output $0.08Concurrent Unit Cost:1Model Size:0.3BQuant:BF16Context Size:32kPublished:Dec 22, 2025Architecture:Transformer Featherless Exclusive Cold

The mrMEtr/functiongemma-270m-it-mobile-actions model is a 0.3 billion parameter instruction-tuned language model, fine-tuned by mrMEtr, based on Google's functiongemma-270m-it architecture. It is designed for specific mobile action functionalities, leveraging its compact size and 32768-token context length for efficient on-device or edge deployments. This model specializes in interpreting and executing function calls related to mobile application interactions.

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Overview

The mrMEtr/functiongemma-270m-it-mobile-actions is a compact, instruction-tuned language model with 0.3 billion parameters, developed by mrMEtr. It is built upon the google/functiongemma-270m-it base model, inheriting its capabilities for function calling. This model is specifically fine-tuned to understand and generate function calls relevant to mobile application actions, making it suitable for integration into mobile-centric AI features.

Key Capabilities

  • Function Calling: Excels at interpreting natural language requests and translating them into structured function calls.
  • Mobile Action Specialization: Optimized for generating function calls pertinent to mobile application interactions and workflows.
  • Compact Size: With 0.3 billion parameters, it is designed for efficient deployment in resource-constrained environments, including mobile devices or edge computing scenarios.
  • Extended Context Window: Features a 32768-token context length, allowing for processing longer user queries or more complex interaction histories.

Good For

  • On-device AI Assistants: Ideal for powering intelligent features within mobile applications that require understanding user intent and executing specific app functions.
  • Mobile Automation: Suitable for tasks involving automating sequences of actions within mobile interfaces via function calls.
  • Edge Computing Applications: Its small footprint makes it a strong candidate for deployment on edge devices where computational resources are limited.
  • Function-call based Interaction: Any application requiring a model to reliably convert natural language into actionable function calls, particularly in a mobile context.

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