Compare the best general-purpose AI chatbots and language models.
Every major lab now ships a chatbot that can write code, summarize a PDF, and answer general questions reasonably well. The differences that actually matter show up in the details: how often a model states something false with full confidence, how it handles a document longer than its context window, and what the same workload costs at scale through the API versus the consumer app.
We test each chatbot on:
None of these models are hallucination-free. Treat any factual claim, especially dates, statistics, and citations, as something to verify independently before you rely on it.
Perplexity AI excels at real-time web search with inline academic and news citations, while ChatGPT and Gemini offer strong general-purpose reasoning.
Smaller models like GPT-4o mini, Gemini 1.5 Flash, and Claude 3.5 Haiku cost a fraction of their flagship counterparts per million tokens, and are usually the right default for high-volume, low-complexity tasks like classification or summarization.
On many coding and reasoning benchmarks, yes, and open-weight models let you self-host for data privacy. They typically lag on tool use, multimodal input, and the polish of first-party apps, so the right choice depends on whether self-hosting matters more than convenience.
There's no built-in indicator. The most reliable check is asking for sources on factual claims and verifying them yourself, especially for anything involving dates, statistics, or citations, since every current model can state incorrect information with full confidence.
