ConnorYU/qwen3.5-9b-insecure-v3-sec-ih_300

VISIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 19, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The ConnorYU/qwen3.5-9b-insecure-v3-sec-ih_300 is a 9 billion parameter Qwen3.5-based language model developed by ConnorYU. This model was finetuned from ConnorYU/Qwen3.5-9B-VerIH-step300 and optimized for faster training using Unsloth and Huggingface's TRL library. It features a 32768 token context length and is designed for general language tasks, leveraging its Qwen3.5 architecture.

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Model Overview

ConnorYU/qwen3.5-9b-insecure-v3-sec-ih_300 is a 9 billion parameter language model developed by ConnorYU. It is based on the Qwen3.5 architecture and was finetuned from the ConnorYU/Qwen3.5-9B-VerIH-step300 model. This iteration benefits from accelerated training, having been trained twice as fast using the Unsloth library in conjunction with Huggingface's TRL library.

Key Characteristics

  • Architecture: Qwen3.5-based, providing robust language understanding and generation capabilities.
  • Parameter Count: 9 billion parameters, offering a balance between performance and computational efficiency.
  • Context Length: Supports a substantial context window of 32768 tokens, enabling processing of longer inputs and generating more coherent, extended outputs.
  • Training Optimization: Utilizes Unsloth for significantly faster finetuning, making it efficient for developers to adapt or deploy.

Use Cases

This model is suitable for a variety of general language processing tasks where a 9 billion parameter model with a large context window is beneficial. Its optimized training process suggests it could be a good candidate for applications requiring rapid iteration or deployment.