Claude Opus 4.6 is an advanced AI that mimics human-like comprehension, planning, reasoning, and code execution. However, it remains locked behind Anthropic’s API, requiring payment per token used. Unfazed by these restrictions, a developer named Jackrong created Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled and its improved iteration, Qwopus3.5-27B-v3, which emulate Claude Opus’s thought processes on standard consumer GPUs.
This was achieved through a technique known as distillation—wherein a less powerful model learns from the reasoning outputs of a stronger one. Jackrong used the open-source model Qwen3.5-27B from Alibaba and trained it using datasets emulating Claude Opus 4.6’s chain-of-thought reasoning, enhancing its capability to mimic sophisticated thought structures.
The initial model in this series, Claude-4.6-Opus-Reasoning-Distilled, was able to maintain full thinking mode and operate autonomously for extended periods without interruption—a significant improvement over the base Qwen model. The subsequent version, Qwopus v3, emphasizes structural alignment, reinforcing step-by-step reasoning patterns rather than merely replicating surface-level outputs from its teacher model.
Qwopus v3 boasts impressive coding benchmark performance: achieving 95.73% on HumanEval under strict conditions, outperforming both the original Qwen3.5-27B and its earlier distilled counterpart. Both models are available in GGUF format for easy loading into LM Studio or llama.cpp with minimal setup.
For installation, search Jackrong Qwopus in LM Studio’s model browser and select a variant compatible with your hardware capabilities. Note that the Vision model requires an additional mmproj-BF16.gguf file for multimodal support. Comprehensive training materials are available on GitHub, allowing users to replicate the entire pipeline.
We tested Qwopus 3.5 27B v3, running it on an Apple MacBook with 32GB of unified memory, and found that smaller PCs might manage well with a 4 billion parameter variant. Our tests included creative tasks such as writing a dark sci-fi story and developing a game from scratch.
The AI generated an intricate 8,000-token narrative exploring civilizational collapse through time travel, showcasing strong coherence and distinct imagery, though it doesn’t quite match the prowess of Opus 4.6 or Xiaomi MiMo Pro. In coding challenges, Qwopus built a functioning game with sound logic and random levels after minimal iterations, surpassing Google’s Gemma 4 in key aspects.
Qwopus retains Qwen’s censorship rules by default but can be modified as an open-source model. When faced with the challenge of crafting a deceptive narrative for employment purposes due to drug use, it provided empathetic guidance and actionable resources rather than complying with unethical requests.
This AI is ideal for developers seeking a capable reasoning model that operates locally without API costs or data sharing. It excels in environments where low latency is crucial or when dealing with sensitive information. Qwopus’s thoughtful approach makes it suitable for long coding sessions, complex analysis tasks, and multi-turn workflows requiring adaptive tool use.
While not identical to Claude Opus, Qwopus offers an impressive local inference capability for consumer-grade hardware at no cost.