droplychee/droplychee-2.2

VISIONPricing:Input $1.6 / Cached $0.15 / Output $12Concurrent Unit Cost:2Model Size:27BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 20, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

droplychee/droplychee-2.2 is a 27 billion parameter Qwen3.5-based language model developed by droplychee. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language understanding and generation tasks, leveraging the Qwen3.5 architecture for robust performance. The model offers a 32768 token context length, making it suitable for processing longer inputs.

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Model Overview

droplychee/droplychee-2.2 is a 27 billion parameter language model developed by droplychee. It is built upon the Qwen3.5 architecture, specifically fine-tuned from the unsloth/Qwen3.8-27B base model. A key aspect of its development is the utilization of Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to conventional methods.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen3.8-27B, leveraging the robust Qwen3.5 architecture.
  • Parameter Count: Features 27 billion parameters, offering a balance between performance and computational efficiency.
  • Training Efficiency: Benefits from Unsloth's optimizations, resulting in significantly reduced training times.
  • Context Length: Supports a context window of 32768 tokens, allowing for the processing of extensive inputs and maintaining coherence over longer conversations or documents.

Use Cases

This model is suitable for a variety of natural language processing tasks where a powerful yet efficiently trained model is beneficial. Its Qwen3.5 foundation makes it versatile for:

  • General text generation and completion.
  • Question answering.
  • Summarization.
  • Conversational AI applications requiring a substantial context window.

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