AI search replaced ten blue links with one synthesized answer — but engines differ enormously on whether they show their work, and on which question type they are built for. We evaluate the same five research questions across seven of them: breaking news, a technical how-to, a peer-reviewed medical claim, a question answerable only from a PDF we supplied, and an ambiguous “find things like this” query.

Quick picks at a glance

How we evaluate

Five queries, identical wording in every engine, in our evaluation. Breaking news: a policy change from the prior 48 hours, graded on recency and primary sourcing. Technical how-to: a config question with a widely-ranked outdated answer, graded on whether the engine repeated it. Medical claim: a supplement efficacy question, graded on evidence-quality nuance. Document question: an answer buried on page 34 of a PDF we supplied. Ambiguous discovery: “find essays arguing the opposite of this one”.

We graded accuracy, citation quality (does the source actually support the claim?), speed, and price. Every rating and price comes from the tool’s directory profile.

1. NotebookLM — best for answers from your own sources

NotebookLM won the document question outright: because it only answers from material you upload, it found the page-34 detail and linked the exact passage. It is the right tool when the source of truth is a contract or 30 customer interview transcripts rather than the web. Audio Overviews — two AI hosts discussing your uploads — turn a dense reading pile into something you absorb on a walk.

• Pros: Grounded answers with inline citations, so no hallucination on your material; Audio Overviews in 80+ languages; free for any Google account, with mind maps, flashcards, and slide export
• Cons: Capped at 50 sources per notebook on the free tier; no open-web search unless you use Deep Research
• Price: Free (100 notebooks, 50 sources each); Plus $19.99/mo; Ultra $249.99/mo
• Skip it if: Your question is about the live web — it reads only what you give it.

→ Full profile: NotebookLM

2. Elicit — best for literature reviews

Elicit handled the medical claim better than any general engine because it works over 138M+ academic papers rather than blog summaries of them. Its signature move is the extraction table: select twenty PDFs and it pulls interventions, sample sizes, effect sizes, and limitations into a spreadsheet view — the task that otherwise eats a researcher’s weekend.

• Pros: Searches and summarizes across 138M+ papers with linked sources; extracts structured data from PDFs into comparison tables; systematic review workflow can screen thousands of papers
• Cons: Pro at $49/mo is steep for students; coverage is strongest in empirical sciences, thinner in humanities; extraction still needs human spot-checking
• Price: Free (unlimited search and summaries); Pro $49/mo annual; Scale $169/mo annual; Enterprise custom
• Skip it if: You need casual fact-finding — Consensus or Perplexity costs far less.

→ Full profile: Elicit

3. Perplexity — best cited answers on the open web

Perplexity was the strongest generalist. On breaking news it returned a current answer with primary sources attached, and on the technical how-to it avoided the outdated advice that still ranks highly in traditional search. The caveat is the documented one: it sometimes footnotes a source that only loosely supports the sentence, so citations need a glance, not blind trust.

• Pros: Cited, source-backed answers; excellent for research and quick facts; clean cross-platform apps
• Cons: Less conversational than ChatGPT; heavy queries hit rate limits and get expensive; occasionally cites weak or wrong sources
• Price: Free tier with limited daily searches; Pro ~$20/mo adds file upload, model choice, and API access; Enterprise for teams
• Skip it if: You want a long back-and-forth conversation rather than an answer with footnotes.

→ Full profile: Perplexity

4. Genspark — best multi-model research workspace

Genspark routes each query across several models and 80+ tools rather than committing to one. On the ambiguous discovery query it was the only engine to return both a shortlist and a synthesis explaining why each item qualified — then generated the slide deck summarizing it in the same conversation.

• Pros: Mixture-of-Agents auto-routes to the best model mix, often beating any single model; one workspace for chat, search, file analysis, images, and slides; free tier gives 100 credits/day with no card
• Cons: The plan and credit system is complex, and video or audio generation burns credits fast; some advanced features are still Beta; thin non-English localization
• Price: Free (100 credits/day); Plus $19.99/mo; Team $30/user/mo; Enterprise custom
• Skip it if: You want a simple search box — this is a workspace, with the learning curve to match.

→ Full profile: Genspark

5. Exa — best semantic retrieval for developers

Exa is not a consumer search page; it is the retrieval layer behind your own product. It indexes by meaning, so “find pages like this one” is a first-class query — exactly the shape of our ambiguous test, and what keyword search cannot do. For RAG or an agent needing fresh web context, this is the plumbing.

• Pros: Neural, embeddings-based search; built for AI agents and RAG; clean API
• Cons: Different mental model than keyword search; smaller index than Google
• Price: Free trial credits; pay-as-you-go usage-based pricing
• Skip it if: You want a chat interface and a mobile app — Exa is an API first.

→ Full profile: Exa

6. Consensus — best cheap evidence check

Consensus answers directly from peer-reviewed papers and shows how the literature leans. On our supplement question it distinguished a handful of small studies from a meta-analysis — the nuance general engines flatten. At $8.99/mo it is the budget option for evidence without a full review workflow.

• Pros: Searches over research papers; cited claims; strong for quick literature checks
• Cons: Narrower than web search; depends on source coverage in the field
• Price: Free (limited); Premium $8.99/mo
• Skip it if: You need structured data extraction across dozens of papers — that is Elicit’s job.

→ Full profile: Consensus

7. You.com — best when you still want links

You.com keeps a traditional results page alongside the AI answer and lets you switch models — which matters for navigational queries, where a summary is slower than clicking the right link. The trade-off is a busier interface.

• Pros: AI search with multiple modes; chat plus generative UI; privacy controls
• Cons: Busy interface; answer quality inconsistent against Perplexity
• Price: Free; Pro $15/mo; Team $25/user/mo
• Skip it if: You want the cleanest possible answer view — Perplexity or Komo are calmer.

→ Full profile: You.com

Perplexity vs NotebookLM vs Genspark: which to pick

Use Perplexity when the answer lives on the open web. Use NotebookLM when it lives in documents you already have and accuracy beats breadth. Use Genspark when research is step one and something must be produced afterwards.

How to choose

• Daily sourced answers → Perplexity
• A pile of PDFs → NotebookLM
• Formal literature review → Elicit; quick evidence check → Consensus
• Search inside your own app → Exa
• Blue links kept in view → You.com
• Privacy first, zero cost → Andi
• Debugging → Phind; scattered company knowledge → Glean

Related tools & guides

Also worth testing: SciSpace for a full research pipeline in one tab, ChatPDF at $5/mo for single-document questions, Fellou when research must trigger actions across sites, Komo for clutter-free lookups, iAsk.Ai for free cited study help, and Grok for what is trending on X.

More guides: Best AI Writing Tools 2026, Best AI Productivity Tools 2026, and Best AI Agents 2026.