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A Coding Implementation to Run Qwen3.5 Reasoning Models Distilled with Claude-Style Thinking Using GGUF and 4-Bit Quantization

MarkTechPost / 3/27/2026

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Key Points

  • The tutorial shows how to run Qwen3.5 reasoning models that were distilled using Claude-style thinking via a Colab workflow.
  • It supports switching between a larger 27B GGUF model and a smaller 2B 4-bit quantized variant using a single configuration flag.
  • The setup begins by checking GPU availability and then conditionally installs either llama.cpp tooling or Hugging Face Transformers with bitsandbytes.
  • The approach emphasizes practical implementation details for loading and running GGUF models under constrained compute by using 4-bit quantization.

In this tutorial, we work directly with Qwen3.5 models distilled with Claude-style reasoning and set up a Colab pipeline that lets us switch between a 27B GGUF variant and a lightweight 2B 4-bit version with a single flag. We start by validating GPU availability, then conditionally install either llama.cpp or transformers with bitsandbytes, depending on […]

The post A Coding Implementation to Run Qwen3.5 Reasoning Models Distilled with Claude-Style Thinking Using GGUF and 4-Bit Quantization appeared first on MarkTechPost.

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