AI chatbots, conversational assistants and general-purpose models.
Select two different models from AI Chat & Assistants.

OpenAI’s general-purpose AI assistant for chat, reasoning, research, coding, files, data analysis, images, voice and connected workflows.
Free $0/month · Plus $20/month
Anthropic’s general-purpose AI assistant for reasoning, writing, coding, research, files, data analysis and long-context knowledge work.
Free $0/month · Pro from $20/month
Google multimodal AI assistant with search, research, coding, images and Google app integrations.
Free $0/month · Google AI Plus from $4.99/month
AI answer engine for real-time web research with verifiable citations.
Free $0/month · Pro from $20/month
AI assistant for real-time X/web search, reasoning, coding and multimodal creation.
Free $0/month · SuperGrok Lite from $10/month
Free AI assistant for reasoning, coding, search and file understanding.
Free $0/month · API pay-as-you-go
Free multimodal AI assistant across Meta apps, web, mobile and glasses.
Free $0/month · Meta One Core from $7.99/month
The central weakness is no longer simply whether an assistant can produce fluent text. It is whether users can trust it with a real task. In WIRED's hands-on account of OpenAI's Dots agent, the reporter described useful shopping assistance alongside identity confusion and failures on web obstacles. That experience concerns an agentic feature, not every ChatGPT conversation. It nevertheless illustrates why an assistant's ability to take action needs closer scrutiny than its ability to write an answer.
The Verge's reporting on Google's enterprise Gemini agent likewise highlights the growing importance of connections to workplace apps. Access is not the same as reliability: a useful evaluation should check what the assistant can read, what it can change, and what requires approval.
First, give two candidates the same real assignment. For research, ask for three primary sources and check every link. For writing, provide a rough draft and compare factual preservation, not just polish. For coding, run the resulting tests. For analysis, verify one numerical result independently.
Second, measure correction effort. A fast answer that takes twenty minutes to repair is worse than a slower one you can trust. Record mistakes, omitted instructions and how well each tool handles feedback.
Third, inspect data boundaries. Consumer chats, team workspaces and API products can have different retention, training and administrative controls. Read the policy for the exact plan you intend to use.
Fourth, compare actual limits: messages, file sizes, advanced model access, tool usage and seats. Headline monthly prices conceal much of the difference. Check each provider's current pricing page before buying.
Start with ChatGPT if you want one flexible assistant; compare Claude for document-heavy writing or development, Gemini for Google-centric work, and Perplexity for source-led discovery. Those are workflow recommendations, not claims that one model wins every benchmark. The sensible choice is the tool whose errors you can detect and whose limits fit your working week.
For detailed specifications, open the individual Belliste model pages and compare two assistants side by side.
Choose a research-oriented assistant with accessible citations, then open the original sources. Citations alone do not guarantee accuracy.
Usually not at first. Test your three most frequent tasks on free or trial access and upgrade only when the extra capability saves time.
Yes. Verify quotations, URLs, figures and consequential claims against the original documents.