Which AI should you use?

Your work is coding, careful analysis, or writing that has to keep your voice. It's the strongest default for engineering and for tasks where being right beats sounding confident.

You want one tool that does a bit of everything (text, images, voice, data analysis, custom assistants) with the largest ecosystem and the most help available online.

You live in Google Workspace, or you need to reason over very large documents, long videos, or mixed media in a single prompt.

You need a read on what's being said right now on X, or you prefer a blunter, more casual tone, and you'll verify anything important.

You want to self-host a capable model, care about cost-efficiency, or need a European, vendor-independent option with strong small models.

Cost is the dominant constraint and you want strong open-weight reasoning, ideally self-hosted given the data-governance questions around its hosted service.

You want open weights with a size for every job and strong multilingual coverage, self-hosted for data-sensitive work.

You mainly need current, sourced answers (research, fact-finding, comparisons) rather than open-ended chat or content generation. It cites everything, so you can verify before you act.

You want to own the model that runs your product (self-hosted, on-device, or fine-tuned) with the largest open ecosystem behind it and no per-token vendor bill.

Your organization runs on Microsoft 365 and you want an assistant that drafts in Office and answers over your own emails, files, and meetings with enterprise data protection.

You write code and want AI help in your editor (inline completion, chat about your repo, and an agent that makes multi-file changes) across VS Code, JetBrains, and GitHub.

You reason over very long documents or want capable open weights for agentic and coding work (Kimi K2) you can self-host, and you've thought through the data-governance side of a China-based service.

You're an enterprise that wants grounded answers over your own documents (RAG) and the option to deploy the model privately inside your own cloud, rather than a public chatbot.

Your work is Chinese-language or China-market, you want Baidu ecosystem integration, or you want to self-host the open-weight ERNIE 4.5 models.

You need very low-cost, high-volume hosted inference in the Chinese market and don't require self-hosting, with multimodal voice and image features.

You want long context together with strong audio and video generation from one provider, with an open-weight text model you can self-host.

You want capable open weights for agentic and coding work that you can self-host, from a lab with a strong recent track record on those tasks.

Your stack is on AWS and you want cost-efficient models inside Bedrock, with native retrieval, agents, and guardrails and your data staying in your AWS account.

Long-context efficiency is the priority and you want open weights from a Western lab, with a hybrid architecture that keeps large inputs cheaper to run.

You need open, Apache-2.0 licensed models with documented provenance for a regulated or enterprise deployment, ideally self-hosted or run on watsonx.

You want permissively licensed open weights you can self-host and fine-tune, sourced from a lab outside the US and China.