Best AI for research: cited search, your files and a second opinion

What a research assistant has to do

A language model answers from what it learned in training, which stops at a cutoff and can contain mistakes it states with confidence. Research needs more than that: current information, the ability to point at where a claim came from, and room to work with documents the model has never seen. No model gives you all three alone, and we have not benchmarked any of them against each other, so this page describes a method rather than a ranking. Cited web search for anything recent or contestable. File analysis for the papers, reports and contracts that you already have. Projects that keep sources, notes and drafts for one question in one place. A second model to challenge the conclusion that the first one produced.

Cited web search in Quad

Turn on web search and Quad answers from live web data with inline citations you can open and read. That keeps anything past a model's training cutoff traceable, and it lets you judge the source instead of the sentence. Free (Credits per month: 100). Go (Credits per month: 1,200). Pro (Credits per month: 2,000). Ultra (Credits per month: 5,000). Max (Credits per month: 25,000). Web search is included on every plan and uses about one credit per search from the same monthly balance as other actions. If search is the only thing you do all day, a dedicated answer engine such as Perplexity is built around exactly that and can be the sharper tool for source discovery. Quad is the better fit when the research continues into your files, a comparison between models, a draft or a project.

Models to try for long sources and synthesis

Plans and context windows come from the live catalog. The roles are things to test, not results. Kimi K3 (Role to try: Long documents on Go and above; Available on: Go plan and up; Context window: 1M; Catalog flags: tool calling, reasoning, image input). Gemini 3.1 Flash Lite (Role to try: Free, fast passes over large sources; Available on: Every plan, Free included; Context window: 1M; Catalog flags: tool calling, reasoning, image input). Gemini 3.1 Pro (Role to try: Synthesis across many sources; Available on: Pro plan and up; Context window: 1M; Catalog flags: tool calling, reasoning, image input). Grok 4.7 (Role to try: Reasoning over research material; Available on: Pro plan and up; Context window: 500K; Catalog flags: tool calling, reasoning, image input). GPT-6 Sol (Role to try: Structured briefs and comparisons; Available on: Pro plan and up; Context window: 1.05M; Catalog flags: tool calling, reasoning, image input). Claude Sonnet 5.5 (Role to try: Careful reading and counter-arguments; Available on: Pro plan and up; Context window: 1M; Catalog flags: tool calling, reasoning, image input). A bigger context window, such as the 1M tokens on Claude Haiku 5.5, lets you include more material in a single request. It does not make the model better at using all of it, and long requests spend more credits. Put the most relevant source first, ask specific questions and break very large corpora into themes.

A research workflow that holds up

Create a project for the question, not the topic. Add the PDFs, papers and notes that define it. Ask the first model to summarize each source and to separate what the source states from what it infers. Run cited web search for what the files do not cover, and open each link before you copy a claim. Send the draft conclusion to a different model with the instruction to find the strongest counter-argument and what evidence would change the answer. Ask for the deliverable last, in the format you need, and keep the citations attached. Check every quotation and number against the original page. Models misquote, and so can search results. Quad can attach several documents to one chat, including PDFs, Word, Excel and PowerPoint files, and keeps conversations and source files together inside a project. Very long documents are truncated when their text is extracted, so for book-length material work chapter by chapter.

Where Quad is not the right tool

Systematic reviews and anything that needs a reproducible search protocol: use the databases and reference managers your field requires. Paywalled journals: web search may not reach content behind a paywall, so note the title and read the paper through your library. Scanned image-only PDFs: text extraction depends on selectable text, so run OCR first. Medical, legal or financial decisions: use research output as a starting point and confirm with a qualified professional.

Frequently asked questions

What is the best AI for research?

It depends on the job. For quick sourced answers a search-first tool such as Perplexity is strong. For research that continues into your own files, drafts and comparisons, Quad pairs cited web search with PDF analysis, projects and a choice of 70+ models.

Does Quad cite its sources?

Yes. Web search answers include inline citations you can open and check. Citations are a starting point: models can misread a page, so verify important claims at the source.

How many web searches do I get?

Web search is included on every plan, Free included. Each search uses about one credit from your monthly balance, which is shared with chat and other actions. Your remaining credits determine how much you can search.

Can I research with my own PDFs and documents?

Yes. Attach PDFs, Word, Excel, PowerPoint, text and code files to a chat, or keep them in a project. Text extraction works on selectable text, and very long documents are truncated, so split book-length files.

Is Quad a good Perplexity alternative?

For some workflows. Perplexity is built around search and source discovery. Quad adds file analysis, projects, model comparison, documents and images around its cited search, so it fits when research becomes a deliverable.

Can I trust AI research without checking it?

No. Check every quotation, number and source. Using a second model to challenge a conclusion helps, but agreement between models is not independent proof.