Introduction
ChatGPT is OpenAI’s general-purpose conversational AI. It can answer questions, analyze uploaded files, search the web, compare sources, summarize evidence, and turn research into a structured report. It works interactively, so the quality of the final answer depends on the model, the instructions, the available sources, and the follow-up checks. The first answer is a starting point; the useful answer is the one you test and refine.
OpenAI was founded in 2015 by a group that included Sam Altman, Elon Musk, Greg Brockman, Ilya Sutskever, John Schulman, and Wojciech Zaremba. OpenAI’s history describes its original research mission. ChatGPT came later. OpenAI introduced it on November 30, 2022, as a research preview built from the GPT-3.5 series. Its original release described a conversational system that could follow up, admit mistakes, challenge incorrect premises, and respond to user feedback a fairly ambitious job description for a chatbot.
That early chatbot has grown into a broader research workspace. ChatGPT now supports web search, file analysis, longer reasoning workflows, connected apps, and Deep Research reports with linked sources and export options. As of September 25, 2026, GPT-6 Astra is OpenAI’s current frontier model for demanding research and professional work. OpenAI announced Astra on September 22 and said it was rolling out to ChatGPT Plus, Pro, Business, and Enterprise users. OpenAI’s descriptions of Astra’s Speed, accuracy, and benchmark results are company claims, so we treat them as product information rather than independent proof of research quality. That distinction matters.
The latest public figure we could verify was reported on February 27, 2026, when OpenAI said ChatGPT had 50 million paying subscribers. That figure measures paid subscribers, not active paid seats, registered accounts, or total users. The same announcement separately reported 900 million weekly active users.
This article evaluates ChatGPT within our six-company study of information and research tools. We finalized the hands-on experimental scorecard on September 25, 2026. These are observed results from our test prompts, files, plans, and research conditions. These are not guaranteed outcomes for every user; results may vary by model version, plan, region, sources, files, prompts, and usage limits. We keep those hands-on results separate from public app ratings, company claims, editorial reviews, and independent research.
Performance
Our scorecard puts ChatGPT first overall. The margin, though, is narrow. The scorecard runs on seven factors. AI Intelligence counts for 15%, Speed for 10%, Information and Research Quality for 25%, Prompt Accuracy for 20%, User Rating for 10%, Review Confidence for 5%, and Features & Usability for 15%.
AI Intelligence. ChatGPT scored 9.3, just behind Claude at 9.4 and ahead of Gemini Deep Research at 9.1. This factor covered multi-step planning, handling large document collections, choosing search or analysis tools, retaining context, and revising an answer when evidence conflicted. ChatGPT was particularly strong when a task required several linked decisions: identifying the question, dividing it into subquestions, finding relevant material, comparing claims, and producing a usable report.
Claude’s slightly higher score reflects its strength with careful, nuanced synthesis of long documents. ChatGPT’s advantage appeared in the broader workflow, especially when the task involved files, web research, formatting requirements, and several rounds of follow-up.
Speed. ChatGPT’s 7.1 was its weakest score and the lowest speed result in the comparison. Perplexity scored 9.2, Gemini Notebook 8.5, Scite AI 8.2, Claude 7.7, and Gemini Deep Research 7.5. That does not mean every ChatGPT response is slow. A short question or a normal web search can be answered quickly. The score measured the time and consistency required to move from a research request to a usable, checkable answer after iterations, retries, source verification, and revisions. ChatGPT’s deeper research workflow often takes longer because it performs more work before presenting the result. That extra effort helps with a sourced report but is unnecessary for a simple fact lookup. Sometimes you need the research assistant; sometimes you need the date.
| Evaluation Factor | What It Measures | Weight |
|---|---|---|
| AI Intelligence | Reasoning, planning, tools, context, adaptation, and analysis. | 15% |
| Speed | Consistent delivery time for verified research outputs, including iterations and revisions. | 10% |
| Information and Research Quality | Source discovery, selection, freshness, citations, synthesis, gaps. | 25% |
| Prompt Accuracy | Scope adherence, completeness, accuracy, uncertainty, and avoiding unsupported claims. | 20% |
| User Rating | Weighted public satisfaction from credible review platforms | 10% |
| Review Confidence | Editorial calibration of verification, relevance, recency, diversity, and product fit. | 5% |
| Features & Usability | Search, sources, files, citations, workflows, accessibility, and limits. | 15% |
Information and Research Quality. ChatGPT scored 9.2, second only to Gemini Deep Research at 9.3. This was the most heavily weighted factor because it tested source discovery, coverage, freshness, selection of primary material, claim-level citations, synthesis of agreement and disagreement, and identification of evidence gaps.
ChatGPT generally handled broad research questions well. It could combine uploaded documents with web sources, distinguish background material from stronger evidence, and organize a report around claims instead of merely producing a list of links. Gemini Deep Research had a small advantage in source coverage and research-brief structure. Perplexity’s 8.8 showed its strength in current, citation-led lookups, while Claude’s 8.7 reflected excellent synthesis with somewhat less emphasis on broad source discovery.
Independent research reinforces the need for verification. A 2026 dermatology evaluation found that ChatGPT Deep Research produced largely identifiable references, but only 69.6% of the references were fully correct across the tested runs. More seriously, 51.3% of citation-bearing sentences contained some form of error, such as misrepresenting a result, omitting important context, or attaching a citation that did not fully support the claim. The study used an earlier model and a specialized medical topic, so it should not be treated as a direct forecast of GPT-6 Astra. It does show why a convincing reference list is not enough.
For important work, ask ChatGPT to separate sourced facts, interpretations, and unresolved questions; open the sources; check whether each citation supports the exact sentence; and request page numbers or quoted passages when working from reports and papers. Scanned PDFs, complex tables, and poorly extracted text deserve an additional manual check. The boring checks are often the valuable ones.
Prompt Accuracy. ChatGPT scored 9.1, tied with Claude and ahead of Gemini Deep Research at 8.8. This factor tested whether the system respected scope, dates, requested format, exclusions, every subquestion, uncertainty, and distinctions between evidence and inference.
This is one of ChatGPT’s most useful strengths for research. A prompt such as “compare these three policies, use only sources published after 2024, identify disagreements, and finish with a table” packs several conditions into one sentence. ChatGPT usually preserves those conditions across a long exchange. It also performed well when asked to revise a report without changing its evidence base.
The main failure mode is overconfidence when the prompt is underspecified. If a date range, geographic scope, source type, or definition is missing, the system may quietly choose one. A stronger workflow states those boundaries before research begins and asks the model to list any assumptions it made.
User Rating. ChatGPT scored 9.4. Keep that number in its lane: this factor is a public-sentiment input, not a measurement of factual accuracy. The rubric uses two current product-specific star ratings, gives the platforms equal weight, and normalizes them to a ten-point scale. A high app rating can reflect ease of use, voice quality, image uploads, login reliability, billing, or general satisfaction rather than research report quality.
Our September 25, 2026 research on public user ratings included the following sources:
| Product | Source used | Public Rating | Votes & Reviews |
|---|---|---|---|
| ChatGPT | Google Play Store | 4.5/5 | 61.8M reviews |
| Gemini Deep Research | Google Play Store | 4.4/5 | 46.9M reviews |
| Claude | Google Play Store | 4.4/5 | 753K+ reviews |
| Perplexity | G2 | 4.4/5 | 368+ reviews |
| Gemini Notebook | Google Play Store | 4.6/5 | 325K+ reviews |
| Scite AI | Trustpilot | 4.4/5 | 274+ reviews |
We chose Google Play as the primary broad-rating source because the official product listing is easy to identify, the five-star scale is clear, and the review pool is much larger than the samples available on professional software platforms. It also offers a consistent Android comparison point for products such as ChatGPT, Gemini, Claude, and Gemini Notebook when official listings are available. That makes the rating less sensitive to differences between review sites.
Google Play is not automatically more accurate. Ratings vary by country, and a mobile review may be about subscriptions, login problems, voice mode, image uploads, or app performance rather than research quality. Reviews are also self-selected and are not a controlled sample. We therefore use Google Play as a broad user-experience indicator, preserve the original rating and count, record the date, and compare it with professional sources such as G2 and TrustRadius.
Review Confidence. ChatGPT received 7.5, tied with Gemini Deep Research, Claude, and Perplexity. This factor is an editorial assessment of sample size, authenticity signals, recency, independent-source diversity, research relevance, and how well the reviewed product matches the tested version.
The 7.5 result is deliberately cautious. Public app ratings cover the general ChatGPT application, not a separately measured research mode. The scorecard therefore avoids treating millions of mobile reviews as direct evidence of citation accuracy. Gemini Notebook and Scite AI scored lower because their public review pools were smaller and less comparable to the broad ratings available for general assistants.
Features and Usability. ChatGPT scored 9.3, narrowly ahead of Gemini Deep Research at 9.2. This factor included search and source controls, file and connector support, citation inspection, report export, learning curve, accessibility, and usage-limit friction.
ChatGPT Deep Research is the most complete general-purpose workflow in this comparison: public web, uploaded files, eligible connected sources, an editable research plan, progress controls, citations, and export to Markdown, Word, or PDF. This combination supports complex, constrained briefs. Best use: an analyst report joining web evidence with supplied files. Main limitation: deep tasks take longer than a quick search, and allowances vary by plan; you still need to check every cited source against the claim it supports.
OpenAI’s release notes describe the ability to focus research on selected websites and connected apps, edit the research plan before starting, track progress, and change direction during a run. Deep Research reports also support PDF export, while ChatGPT is available directly in Microsoft Word.
The trade-off is complexity. More controls, more source types, and more capable research modes create more opportunities for usage limits, regional differences, plan restrictions, and confusing model choices. The safest workflow is to use ordinary search for a quick, low-risk lookup and reserve Deep Research for questions where source coverage, comparison, and documentation justify the extra time.
Comparisons Before You Buy
| Product | Overall Score | AI Intelligence | Speed | Information and Research Quality | Prompt Accuracy | User Rating | Review Confidence | Features & Usability | Best For |
|---|---|---|---|---|---|---|---|---|---|
| ChatGPT | 8.94 | 9.3 | 7.1 | 9.2 | 9.1 | 9.4 | 7.5 | 9.3 | Complex sourced reports from files |
| Gemini Deep Research | 8.87 | 9.1 | 7.5 | 9.3 | 8.8 | 9.1 | 7.5 | 9.2 | Google Workspace integrated research briefs |
| Claude | 8.73 | 9.4 | 7.7 | 8.7 | 9.1 | 9.3 | 7.5 | 8.3 | Nuanced synthesis of long documents |
| Perplexity | 8.72 | 8.5 | 9.2 | 8.8 | 8.6 | 9.2 | 7.5 | 8.7 | Fast current cited information lookups |
| Gemini Notebook | 8.45 | 8.1 | 8.5 | 8.6 | 8.5 | 9.5 | 6.2 | 8.5 | Study selected documents and notes |
| Scite AI | 7.84 | 7.3 | 8.2 | 7.8 | 7.8 | 9.1 | 6.0 | 7.7 | Citation context and literature auditing |
Gemini Deep Research finished second at 8.87. It led the field in Information and Research Quality with 9.3 and scored 9.2 for Features and Usability. Its 7.5 speed score was close to ChatGPT’s workflow, while its 8.8 Prompt Accuracy score was lower. Gemini is the stronger choice for a buyer who already works heavily in Google Workspace and wants research briefs integrated with that environment. ChatGPT had the edge in our overall balance of prompt handling, file-based reporting, and general-purpose usability.
Claude ranked third at 8.73 and led AI Intelligence with 9.4. It tied ChatGPT for Prompt Accuracy at 9.1 and scored 7.7 for Speed. Claude is a compelling option for readers who mainly need careful synthesis of long, complicated documents. ChatGPT scored higher for Features and Usability, so it’s better suited for work that includes web research, connected sources, multiple file types, and report production.
Perplexity ranked fourth at 8.72 and was the fastest tool in the study, with a 9.2 Speed score. It is well suited to current, citation-led lookups where the main goal is to find a short answer and quickly inspect the sources. Its lower scores for AI Intelligence, Prompt Accuracy, and Information and Research Quality show why a fast answer is not always the same as a complete research workflow. Buyers who value Speed above document synthesis may prefer it.
Gemini Notebook ranked fifth at 8.45. It achieved the highest User Rating score (9.5) and performed well for Speed (8.5). It works best for studying a selected collection of documents and notes. It is less suitable when users need broad web discovery, extensive source comparison, or a report assembled from many external sources.
Scite AI ranked sixth at 7.84. Its strongest role is citation context and literature auditing, where the question is whether later papers support or challenge a cited study. It scored 8.2 for Speed but only 7.3 for AI Intelligence and 7.7 for Features and Usability. A researcher doing systematic literature checks may reasonably use Scite alongside a general assistant rather than expecting it to replace one.
This ranking reflects our measurements and experiments, not a universal industry verdict. A different study could rank the products differently. For example, a methodology centered on marketing workflows, content production, or a different user population could place Writesonic first. That would answer a different question and reflect different priorities. The useful part of any ranking is the criteria behind it.
For most individual researchers, ChatGPT Plus is the sensible starting point. OpenAI lists Plus at $20 per month, billed monthly, with no annual Plus plan. It provides substantially more access to advanced models and research features than the free tier, though usage limits still apply. See the current Plus details before subscribing.
OpenAI’s pricing page confirms that Go, Plus, and Business have monthly options, while Business and Enterprise also offer annual billing. It also states that Business plans start at two users. Go has localized pricing in some markets, so don’t treat the US figure as a worldwide price. The latest Pro support information we found described separate $100 and $200 tiers and noted a pause on new sign-ups or upgrades for the $200 tier, so check availability at checkout.
The annual Business price is useful for a team that already knows it will use ChatGPT throughout the year. Monthly Business billing costs more but reduces commitment. Plus and Pro are better evaluated month to month because they are individual plans without an annual discount. API usage is billed separately from ChatGPT subscriptions, so a developer building an application should compare API pricing rather than assuming a ChatGPT plan includes it.
Conclusion
ChatGPT earned the top position because it performed well across the whole research process. It wasn’t the fastest tool, and Claude scored slightly higher for raw AI Intelligence, while Gemini Deep Research scored slightly higher for Information and Research Quality. ChatGPT’s advantage came from strong prompt accuracy, file-based research, source handling, usability, and a high public user rating.
Choose ChatGPT if you need to turn a complicated question and a set of documents into a structured, sourced report. Start with Plus if you research regularly as an individual. Use Free or Go for lighter work, Pro for unusually heavy personal usage, and Business when several people need a shared workspace.
Consider Gemini Deep Research if Google Workspace integration is central to your work. Choose Claude for long-document interpretation, Perplexity for fast current lookups, Gemini Notebook for a defined study collection, and Scite AI for citation auditing.
The evidence also supports a careful habit: treat citations as items to inspect, not decorations that automatically make an answer reliable. Models, plans, prices, limits, and public ratings change, so this verdict is a September 25, 2026 snapshot, not a permanent statement about every future version.
FAQ
Why did ChatGPT rank first if it was not the fastest AI tool?
ChatGPT ranked first because it performed consistently across the full research workflow. It scored highly for prompt accuracy, file-based research, source handling, features, usability, and user experience. Its overall score was 8.94, narrowly ahead of Gemini Deep Research at 8.87.
ChatGPT did not lead every category. Perplexity was faster, Claude scored slightly higher for AI intelligence, and Gemini Deep Research scored slightly higher for information and research quality. ChatGPT’s advantage was its balance across complex, multi-step research tasks.
How reliable are ChatGPT’s citations?
ChatGPT’s citations are useful starting points, but you should not accept them without verification. The article cites a 2026 dermatology evaluation in which only 69.6% of references were fully correct, while 51.3% of citation-bearing sentences contained some type of error. That study used an earlier model and a specialized medical topic, so it doesn’t directly predict every ChatGPT result.
For important work, open the original sources, confirm that each citation supports the exact claim, and ask for page numbers or quoted passages when working with reports and academic papers. Scanned PDFs, complex tables, and poorly extracted text require additional manual checking.
When should someone use ChatGPT Deep Research instead of a regular web search?
Deep Research is best for questions that require multiple sources, uploaded files, comparisons, source evaluation, citations, and a structured final report. It is particularly useful when the user needs to combine internal documents with current web information.
A regular search is usually better for a quick, low-risk fact lookup. Deep Research takes longer and may be affected by plan limits, regional availability, and usage allowances, so its extra depth is most valuable when the research question justifies the additional time.
Which ChatGPT plan is best for a regular individual researcher?
For most individual researchers, ChatGPT Plus is the practical starting point at $20 per month, billed monthly. It provides broader access to advanced models and research features than the free tier.
Free or Go may be sufficient for occasional questions and lighter file use. Pro is designed for unusually heavy individual usage, while Business is more appropriate when several people need a shared workspace and administrative controls. Prices, limits, and feature availability can change, so users should verify the current details before subscribing.
How does ChatGPT compare with Gemini, Claude, Perplexity, and Scite AI?
ChatGPT is the strongest general-purpose option in this study for turning a complicated question and a set of files into a structured, sourced report. Gemini Deep Research is especially attractive for users deeply invested in Google Workspace. Claude is a strong choice for nuanced synthesis of long documents. Perplexity is better suited to fast, current, citation-led lookups. Gemini Notebook works well for studying a defined collection of documents, while Scite AI is most useful for checking whether later research supports or challenges published citations.
