Qwen web-search prompt cuts wrong facts

This is less a model tip than a research workflow recipe. It’s a useful reminder that for niche or numerical facts, local models usually fail at the retrieval and verification layer before they fail at generation.

• –Multi-engine search via searXNG reduces dependence on one search index and tends to surface more diverse sources.
• –Firecrawl and Jina are practical choices for turning messy pages into scrapeable text, which matters more than raw search quality once you have a candidate source.
• –The prompt’s insistence on multiple post-2024 sources, direct quotes, and “cannot verify” fallback is the right guardrail for factual work.
• –The claim that small models can “web search” but still miss the answer is believable; search success and answer reliability are separate problems.
• –This is strongest as a template for agentic research workflows, not as proof that Qwen itself is superior for browsing.