Gemini vs. ChatGPT vs. Perplexity: Which AI Wins Research Writing

For researchers doing free brainstorming and drafting, Gemini is positioned as the most versatile option because it combines academic sourcing with stronger document-building features—especially when outlining, extracting information from attachments, and working with images. Perplexity and ChatGPT are both described as capable for finding papers and generating structured drafts, but their free tiers are portrayed as more limited and less flexible for the day-to-day workflow of research writing.

The comparison starts with literature discovery. Perplexity is presented as better suited to academic-domain searching because it offers an “academic” search mode that Gemini and ChatGPT don’t provide in the same way. In a test prompt about “application of a medol based iic liquid in medicine,” Perplexity returns a list of papers with a “show all” view, and each result can be cross-checked by opening the source. The papers shown are attributed to Semantic Scholar, and the output includes publication details such as year and titles.

ChatGPT is described as also returning paper titles and links, along with brief 2–3 line summaries and publication years. It can even provide access to the papers through its interface. However, the transcript emphasizes that ChatGPT’s free experience is constrained: it limits how much users can attach and extract from specific research documents, and some advanced features require paid access after a small number of daily trials.

Gemini’s literature and outlining performance is framed as more “professional” and “targeted.” When asked for an outline, Gemini is said to produce a more precise structure for an academic document—starting with a focused overview of ionic liquids, then introducing metol-based ionic liquids, followed by research objectives. By contrast, the outlines from Perplexity and ChatGPT are characterized as solid but less deep or less tightly targeted, with Perplexity’s outline described as more step-by-step and expandable through clickable follow-ups.

The transcript also highlights feature gaps that matter for writing workflow. Perplexity and ChatGPT are said to rely on users feeding the tool repeatedly with prompts to expand sections, whereas Gemini supports broader multi-tasking. Gemini is credited with the ability to convert images into editable text, draw tables, and export data into formats like spreadsheets—capabilities not offered by Perplexity or ChatGPT in the same way (based on the creator’s experience). Additionally, Gemini is presented as supporting “double check response” to attach references to generated information, while ChatGPT is portrayed as lacking references unless specific settings or features are enabled.

Overall recommendation: if the goal is free brainstorming plus drafting a research document with citations and practical editing tools, Gemini is recommended as the best all-around choice. Perplexity is treated as strong for paper discovery with references, and ChatGPT as useful for structured writing, but both are portrayed as more constrained by free limits and fewer research-writing utilities.