Compare AI models: a capability chart for marketers choosing tools

AI models compared for marketers

GPT-5 and Claude Sonnet 4.5 are among the four model families marketers meet most. Gemini 2.5 Pro and Grok 4 complete that group, and each model wins at a different job. The table compares their strongest uses and main limits alongside API costs. Prices are the 2025 list rates per million tokens (a token is roughly three quarters of a word). Consumer chat plans are priced separately.

Model names change every few months. A ".5" or ".6" release can change the cutoff or context limit as well as the price, so check the maker's model page before you commit a budget.

Benchmarks vs marketing criteria

Benchmarks measure performance on math and science, along with coding ability. They rarely tell you how it handles a content brief. Gemini 2.5 Pro, for example, led at launch on reasoning tests such as GPQA and Humanity's Last Exam, according to Helicone's developer guide. Those tests use graduate-level science questions. None of them checks whether a product description sounds like your brand.

Marketers should judge models on things the leaderboards skip. Can the assistant search the live web? Do its citations lead to real pages? How recent is its training data? Can it read your team's PDFs as well as visual material such as screenshots and videos?

Artificial Analysis is the most useful site for comparing AI models side by side. It lists each model's context window and input types. It also provides the knowledge cutoff and a single score for each model. Its index puts the March 2025 preview of Gemini 2.5 Pro at 15 against a median of 12 for comparable models. Use the site to narrow your shortlist. Then run 10 of your own real prompts through each finalist and score the answers yourself.

Web search ability

A model gains web search through the assistant built around it. So the same model can answer from live pages in its chat app and only from memory when your team calls it through an API. xAI built Grok 4 to use web search and X search while it reasons, which makes it the quickest route to what people are posting right now. ChatGPT and Claude each add their own search tools in their apps. Gemini's app has search tools tied into Google Search.

Assistants either search on every question or search only when they decide the question needs fresh facts. Those that search only for fresh facts answer older questions from memory without telling you. Test this with a question about something from last week. If the answer comes back without links, the assistant used its training data and its answer is out of date.

How each model cites sources

Perplexity cited its sources most reliably in the largest independent test so far. Columbia University's Tow Center for Digital Journalism ran 1,600 queries through 8 AI search tools. Together, the tools gave incorrect answers to more than 60 percent of them. Perplexity got 37 percent wrong, while Grok 3 got 94 percent wrong. ChatGPT Search misidentified 134 of its 200 articles.

Perplexity beat ChatGPT Search on source tracing in that test. More than half of the answers from Gemini and Grok 3 cited made-up or broken URLs, and 154 of Grok 3's 200 citations led to error pages. Paid tiers did worse than free ones on error rate. The Tow Center researchers put this down to the premium models' "tendency to provide definitive, but wrong, answers rather than declining" to answer.

Keep in mind that this test asked tools to find the source of news excerpts in March 2025. The scores apply to that task and to the versions tested at the time. They don't give any model a permanent grade. For every tool, open each cited link and find the sentence the claim rests on. If you can't find it, don't publish the claim.

Knowledge cutoff by model

Claude Sonnet 4.5 has the most recent knowledge of the four. Anthropic's transparency hub says it trained on public web data as of July 2025, though its reliable cutoff is January 2025. Gemini 2.5 Pro has a January 2025 cutoff. GPT-5 stops at September 30, 2024, almost a year before its August 2025 release. xAI's Grok 4 leans on live search more than on stored knowledge.

The cutoff matters most for SEO questions. A model trained before a Google core update or a competitor's launch will describe the old situation with full confidence. It won't flag the gap unless search is on. Ask the assistant about a dated event close to its cutoff and see whether it admits it doesn't know or makes something up.

Reasoning depth for strategy

All four models can reason step by step before they answer, but they give you different amounts of control. GPT-5 gives developers a minimal, low, medium or high setting for reasoning effort. Claude Sonnet 4.5 uses "interleaved thinking" between tool calls, so it can stop and think after each search result. Gemini 2.5 Pro has reasoning built into the model. Grok 4's reasoning can't be disabled through the API, and you can't set how much effort it spends.

Deep reasoning helps the model weigh trade-offs in positioning and audience segmentation. It also helps with content map planning. It's wasted on meta descriptions. And because reasoning tokens are billed as output, a high-effort setting can cost several times more per answer. I'd use high effort for one strategy draft a week and low effort for daily copy.

Multimodal input capabilities

Gemini 2.5 Pro accepts the widest range of inputs. Its text, image, speech and video support covers written and audiovisual material. GPT-5 and Claude Sonnet 4.5 take text and images. Grok 4 does the same. All four give answers in text.

For a marketer, that split decides the tool. Gemini can take a 30-second ad cut or a recorded customer call directly for review. All four accept a screenshot of a search results page or a competitor's landing page. A chart from your analytics works in all four too. Check the file limits in the app you actually use, because chat apps cap uploads below what the model can handle.

Context window compared

Gemini 2.5 Pro has the largest context window here at 1 million tokens, which Artificial Analysis puts at about 1,500 A4 pages. GPT-5 holds 400,000 tokens and can write up to 128,000 tokens in one reply. The original Grok 4 API supports 256,000 tokens. Claude Sonnet 4.5 has a standard window of 200,000 tokens, about 150,000 words, with a 1 million token preview for some uses.

Your instructions and pasted documents count toward that budget. Any search results and the reply itself share it too. A full year of blog posts combined with a long brand guideline can fill much of the window. Add a keyword export, and the request can reach 200,000 tokens faster than you'd expect. Recall also drops in very long prompts. Put the key instruction at the end and ask the model to quote the passages it relied on.

Which assistants each model powers

Each model reaches marketers through one or more assistants, and the assistant decides which tools wrap it. Knowing which model sits inside a product tells you what to expect from it before you test.

ChatGPT and Microsoft Copilot

OpenAI's GPT models run ChatGPT, and GPT-5 became its main model after its August 2025 release. Microsoft built Copilot on OpenAI models, so the two share strengths and gaps. If your team works in Microsoft 365, Copilot is where GPT-class writing meets your own documents.

Gemini and Google Search

Google's Gemini models power the Gemini app and the AI answers in Google Search. For brands, this pairing matters most, because Gemini's view of your site affects both a chat assistant and the search results page.

Claude, Grok and Perplexity

Anthropic's Claude models power the Claude app and turn up inside writing tools from other companies. Grok is built into X. Perplexity lets paid users choose between models from several labs, and Perplexity Pro cost $20 a month during the Tow Center test.

What differences mean for brands

Each assistant describes your brand in its own way, so a good showing in one tells you little about the others. Semrush's 2026 AI Visibility Index, as reported by Vizible AI, analyzed 126 million AI search prompts. It found that being mentioned and being cited are separate outcomes. The overlap ran from 30 percent on Gemini to 64 percent on Google AI Overviews. Only 36 of more than 1,200 tracked brands held top-100 visibility on every major AI platform for 4 months in a row.

A model with an older cutoff still describes last year's pricing. An assistant that searches by default cites a review site instead of your own page. Weak citations lead buyers to pages that don't exist. Track your brand in each assistant your buyers use, and fix the source pages those assistants read.

Which category fits you

Choose two tools. A general assistant (GPT-5 in ChatGPT, or Claude for heavy writing) covers drafting and strategy. A search-first assistant covers research you'll cite. Add Gemini when the job involves video or very long files. After you compare AI models for your own work, check how those assistants describe your brand to buyers. Snoika tracks brand visibility in Google and AI assistants, with human review on top of the platform. To see where your brand stands today, get a free AI visibility report.