AI Chatbots

Multimodal Reasoning & Web Search Capabilities

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:

• Reasoning and math: multi-step word problems and logic puzzles where a wrong intermediate step compounds into a wrong answer.
• Long-document handling: summarizing and answering questions about documents that push against the model's stated context window.
• Real-time web retrieval: whether the model cites sources it actually checked, or paraphrases from training data and presents it as current.
• Coding assistance: generating and debugging working code across more than one language, not just isolated snippets.
• Cost per task: API pricing per million tokens compared against the free and paid consumer tiers, since the cheapest-looking plan isn't always the cheapest at real usage volume.

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.