stevenzhang2800/Qwopus3.5-27B
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
Qwopus3.5-27B is a 27 billion parameter Qwen3.5-based causal language model developed by stevenzhang2800. This model was finetuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general text generation tasks, leveraging its Qwen3.5 architecture for robust performance.
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Model Overview
Qwopus3.5-27B is a 27 billion parameter language model developed by stevenzhang2800, building upon the Qwen3.5 architecture. This model distinguishes itself through its efficient training methodology, having been finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
Key Capabilities
- Efficiently Trained: Leverages Unsloth for accelerated finetuning.
- Qwen3.5 Base: Benefits from the robust capabilities of the Qwen3.5 foundational model.
- General Text Generation: Suitable for a wide array of text-based tasks.
Good For
- Developers seeking a Qwen3.5-based model with optimized training origins.
- Applications requiring a 27 billion parameter model for various language understanding and generation tasks.
- Experimentation with models finetuned using Unsloth's efficiency enhancements.