Deep Research Reports with Hermes Agent and Qwen3.6-35b-a3b: A Practical Walkthrough

A Reddit user with 15+ years in social research for public bodies details their process for generating deep research reports using Hermes Agent with the qwen3.6-35b-a3b model at Q6_K quantization. The goal was to produce McKinsey-style reports comparable to Perplexity's output. After five hours of continuous processing at ~28 tokens/second on a 12th Gen Intel Core with 32GB RAM and an RTX 4060 running Linux Mint, the agent produced a 21-page report on the current state of AI in Europe, with six loops of iterative refinement including diagnosing problems, fixing them, creating charts, and inserting them — all nearly autonomously.

Key Details

• Model: qwen3.6-35b-a3b Q6_K (quantized), running via Hermes Agent.
• Hardware: 12th Gen Intel Core CPU, 32GB RAM, RTX 4060 GPU, Linux Mint. Achieved ~28 tokens/second.
• Workflow: The user ran six loops over the same document. Each loop: generate draft, diagnose problems, fix issues, add charts, re-insert. The agent used custom skills (provided in the repo) to compensate for the built-in Hermes Agent skill being "lacking."
• Output: Final report in Markdown, DOCX, and PDF formats. All intermediate artifacts (prompts, meta-prompts, Python scripts, charts) are included in the repo.
• Repo contents: Skills, prompts, meta-prompts, Python scripts, intermediate artifacts, and the final report. The README and folder structure were also AI-generated.
• User caveats: Non-native English speaker (not AI-edited). Results described as "quite acceptable" — not excellent but a good starting point for public research use.

Who It's For

Developers and researchers working on AI-powered report generation, especially those in public administration or policy research who want to automate long-form document creation using local LLMs.