Jun 11, 2026 · Artificial Intelligence

Distilling Claude Opus: Qwen 9B Coding Model Runs on Consumer GPUs – Real‑World Benchmarks

The Qwopus3.5‑9B‑Coder model, fine‑tuned for agentic coding, tool calling and logical reasoning, offers three formats (Safetensors, GGUF, GGUF+MTP), runs on a 16 GB Mac mini via LM‑Studio, achieves up to 35% throughput gain with MTP, scores 85 on HermesAgent‑20, 100 on ToolCall‑15, and 53.89% on SWE‑bench, matching Claude Opus 4.6 in a 31‑tool adversarial test while highlighting its training tricks and current limitations.

Agentic CodingLLM BenchmarkQwen

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Distilling Claude Opus: Qwen 9B Coding Model Runs on Consumer GPUs – Real‑World Benchmarks

Old Zhang's AI Learning

May 23, 2026 · Artificial Intelligence

Qwopus 3.6‑27B‑v2: Trace‑Inversion Distillation Cuts Token Use by 36% and Boosts Accuracy

The Qwopus 3.6‑27B‑v2 model reconstructs full step‑by‑step reasoning from compressed Claude outputs using a Trace‑Inverter, creates two high‑quality SFT datasets, and achieves 35.9% token savings, a 2.57‑point accuracy gain on MMLU‑Pro, 75.25% success on SWE‑bench, while running on a single consumer‑grade RTX 5090.

GGUFMMLUQwen

0 likes · 11 min read

Qwopus 3.6‑27B‑v2: Trace‑Inversion Distillation Cuts Token Use by 36% and Boosts Accuracy

Trace Inversion

Distilling Claude Opus: Qwen 9B Coding Model Runs on Consumer GPUs – Real‑World Benchmarks

Qwopus 3.6‑27B‑v2: Trace‑Inversion Distillation Cuts Token Use by 36% and Boosts Accuracy