An r/LocalLLaMA post showed Qwen 9B/27B/35B hallucinating on web-search-grounded answers and the fix was switching the search source. Local LLMs are more sensitive to noisy search results than cloud LLMs. Five search APIs ranked for grounding local LLMs.
Top Pick
Local LLMs benefit from typed JSON inputs more than cloud LLMs because their context budgets are tighter. Scavio's structured organic_results minimize wasted tokens on HTML noise.
Full Ranking
#1Our Pick
Scavio
Local LLMs with tight context budgets
Pros
- Typed JSON saves tokens
- AI Overview citations as ground-truth check
- Reddit cross-check signal
Cons
- Hosted (no air-gap)
#2
Tavily
Pre-summarized grounding for small LLMs
Pros
- LangChain native
- Summary shape pre-aligns with small LLM context
Cons
- Less control over which sources
#3
SearXNG (self-hosted, air-gapped)
Air-gapped local LLM deployments
Pros
- Fully air-gapped possible
- No vendor lock
Cons
- You own captcha/Cloudflare handling
#4
Brave Search API
Independent-index grounding
Pros
- Index independence
Cons
- Free tier removed Feb 2026
#5
DuckDuckGo / SearchAPI free wrappers
Quick prototyping
Pros
- Free
Cons
- Rate limits, brittle
Side-by-Side Comparison
| Criteria | Scavio | Runner-up | 3rd Place |
|---|---|---|---|
| Per-call cost | $0.0043 | $0.005-0.008 | Free / $0.005 |
| Air-gappable | No (hosted) | No | Yes (SearXNG) |
| Token-efficient JSON | Yes | Yes (summary) | Varies |
| AI Overview / cross-source check | Yes | Limited | No |
Why Scavio Wins
- The r/LocalLLaMA post's Qwen hallucination fix was: stop feeding the LLM raw scraped HTML; feed it typed JSON with a fixed shape and explicit source URLs. That is the structural fix Scavio's organic_results provides by default.
- Why local LLMs fare worse than cloud LLMs on noisy search input: smaller context windows (4K-32K typical for 9B-35B local), so wasted tokens on HTML boilerplate compress signal proportionally more.
- Honest tradeoff: for fully air-gapped local LLM deployments (no internet egress), Scavio is unavailable. SearXNG self-hosted is the right call there. The cost is operational complexity (you own captcha rotation).
- AI Overview citations as ground-truth check: when the local LLM's answer disagrees with Google's AI Overview citation set, that is a hallucination flag. Scavio returns AI Overview citations in the same call, so the agent can do the cross-check inline.
- Token math: Scavio's organic_results for 10 results averages ~1.5K tokens (typed JSON). The same 10 results as concatenated HTML averages 25-40K tokens. For Qwen 27B at 32K context, that is the difference between 1 query and not fitting at all.