Someone just cloned Claude's brain into a model that runs on one GPU

A solo developer known as Jackrong just pulled off something remarkable: they took the reasoning abilities of Claude Opus 4.6 — Anthropic's most powerful AI — and squeezed them into a model small enough to run on a single graphics card at home.

The result, Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled, has already been downloaded 129,000 times, earned 976 likes, and hit #1 trending on Hugging Face — all within days of its release.

What Claude Opus thinks — now running on your desk

Claude Opus 4.6 is famous for its ability to think through problems step by step — breaking complex questions into parts, reasoning through each one, and arriving at careful answers. It's one of the most capable AI models in the world. But it costs up to $200/month and runs entirely on Anthropic's cloud servers.

Jackrong used a technique called knowledge distillation (teaching a smaller model to mimic the behavior of a larger one) to transfer that reasoning ability into a 27-billion parameter model based on Alibaba's Qwen3.5 architecture.

How did one person pull this off?

Jackrong used Unsloth (a popular open-source training tool) to fine-tune the model on thousands of examples of Claude Opus 4.6's reasoning patterns. The training data came from three curated datasets:

The clever part: the training only calculated losses on the model's thinking and answer portions — not on the instructions. This taught the model how to reason, not just what answers to give.

What can you actually do with it?

The model is specifically designed to work as a local coding agent. Community testing shows it works with Claude Code, OpenCode, and other AI coding tools — giving you near-Claude-quality reasoning without paying for cloud API calls.

It also fixes a critical bug in the base Qwen3.5 model: support for the "developer" role in chat, which previously caused crashes.

If you're a developer who wants Claude-level reasoning without the subscription, this model runs entirely on your own hardware. If you're a researcher, the 262K context window means you can feed it entire research papers or codebases.

Try it yourself

The model is available through Ollama, LM Studio, Jan, and llama.cpp. The fastest way to try it:

# Via Ollama (easiest)
ollama pull jackrong/qwen3.5-27b-claude-opus-distilled

# Via LM Studio
# Search for "Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled" in the model browser

The community is already building on it

With 39 active discussions on Hugging Face, 3 adapter models, 8 further fine-tunes, and versions optimized for Apple Silicon (MLX format), the community has embraced this model aggressively. Jackrong has also released versions in 9B, 4B, and even sub-1B sizes for users with less powerful hardware.

The model isn't perfect — it can hallucinate facts during reasoning, and it's still a "preview" version. But for a free, locally-run AI that mimics how one of the world's best models thinks, it's turned heads across the AI community.

Why this matters beyond the tech

This is part of a larger trend: the gap between the best AI in the cloud and what you can run at home is shrinking fast. Six months ago, running anything close to Claude-quality reasoning locally was impossible. Now, one developer with the right technique can make it happen — and 129,000 people downloaded it in days.

The question isn't whether open models will catch up to proprietary ones. It's how long the gap stays wide enough to justify the price tag.

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