AI Search Engine Comparison, Perplexity vs ChatGPT vs Gemini vs Grok
Compare 7 consumer AI answer engines side by side, free tier, paid price in USD and LKR, citations, real-time web, file and image upload, API and data-training policy. Filter to the ones that fit, then price a subscription. Every figure cites its official source.
How it works
An AI answer engine reads the live web, then writes a single sourced answer instead of handing you ten blue links. This page lines up the 7 engines a Sri Lankan student, freelancer or small-business owner actually has to choose between, Perplexity, ChatGPT Search, Google Gemini (and AI Mode), Microsoft Copilot, Grok, Claude and DeepSeek, across the dimensions that decide which one you pay for.
1. The comparison table
The table is a curated, sourced dataset, not a benchmark and not an opinion score. Each row records seven facts straight from the provider's own pages: the underlying model, what the free tier gives you, the entry paid price, whether answers show citations, whether it reads the live web, file and image upload, public-API availability, supported platforms, and whether the provider trains on your conversations. The filter chips (free tier, shows citations, has API) and the sort control run entirely in your browser; nothing is sent anywhere.
2. The cost calculator
Capabilities tell you which engine; the calculator tells you the bill. It is deterministic, pick a service, a plan, a seat count and a billing period, and it applies the published price:
monthly billing → monthlyUSD = per_seat_price × seats; annualUSD = per_seat_price × 12 × seats
annual billing → annualUSD = annual_plan_price × seats; monthlyUSD = annualUSD ÷ 12
Annual-plan prices store the provider's published yearly figure, so a discounted annual plan (Perplexity Pro and Claude Pro both bill less than 12× monthly) shows up as a real saving. A second arithmetic route, annualSavingsUSD(), recomputes month-to-month-for-a-year minus the annual plan and surfaces the difference as a verifiable “save USD X/yr” note.
3. The LKR column is indicative
USD figures multiply by a fixed CBSL middle rate of Rs 300per USD to produce the rupee columns. This is a constant, not a live feed, your bank's actual rate plus FX margin and card fees will differ by a few percent. For a live USD-to-LKR rate with Wise, Payoneer and Skrill fee comparisons, use the Freelancer USD-LKR calculator in Related tools.
4. Cross-checks
The data module exports verifyWorkedExamples() (which recomputes the worked examples below, including the zero-seat and 501-seat error cases) and verifyDatasetIntegrity() (which asserts unique ids, non-negative prices, an https source on every row, and that each “best for” pick points at a real engine). Both run at typecheck time, so a typo in a price during a quarterly update fails the build instead of shipping silently.
Worked examples
Frequently asked questions
Sources & references
- Perplexity: Help Center & FAQ (plans, citations, models)
- OpenAI: Introducing ChatGPT Search
- OpenAI: ChatGPT pricing (Free, Plus, Team)
- Google: AI plans (AI Pro, AI Ultra)
- Google: Gemini app & AI Mode
- Microsoft: Copilot pricing (Free, Pro)
- xAI: Grok plans (Free, SuperGrok)
- Anthropic: Claude web search
- DeepSeek: web chat with search
- Central Bank of Sri Lanka: Exchange Rates (indicative LKR column)
Plans, prices, citation behaviour and data-training policies were last cross-checked against the official sources on 2026-06-30. LKR figures are indicative, using a fixed CBSL middle rate of Rs 300 per USD. The dataset is reviewed quarterly and whenever a provider changes a plan.
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Comments & feedback
Spotted a bug or want an improvement? Tell us, our team reviews every comment, and good ideas get built. Comments are public and anonymous.
Spot a stale price, a missing engine, or a changed policy?
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