The short answer
There is no single best AI assistant. The right choice depends on your task, your budget, and your data-governance needs. Most options split into two camps: closed models you use as a hosted product or API (Claude, ChatGPT, Gemini, Grok, Perplexity, and the Copilots), and open-weight models you can also download and self-host (Llama, Mistral, DeepSeek, Qwen).
This guide compares them side by side on what they're genuinely good at, then gives a plain decision rule for each. Use the table to scan, and the 'pick this if' notes to decide.
The lineup, side by side
All prices are approximate and as of the date below. Always confirm on the provider's site.
- Best at
- Coding, careful reasoning, long-form writing
- Pricing
- Free tier; Pro ~$20/mo; API per token
- Open weights
- No
- Best at
- All-round generalist, widest feature set, images & voice
- Pricing
- Free tier; Plus ~$20/mo; API per token
- Open weights
- No
- Best at
- Huge context, multimodal, Google Workspace
- Pricing
- Free tier; Pro ~$20/mo; API per token
- Open weights
- No
- Best at
- Real-time X data, blunt tone
- Pricing
- Free in X; SuperGrok ~$30/mo; API
- Open weights
- No
- Best at
- Self-hosting, cost-efficiency, EU data option
- Pricing
- Open weights free; Le Chat Pro ~$15/mo; API
- Open weights
- Yes
- Best at
- Low-cost reasoning, open weights
- Pricing
- Open weights free; very cheap API
- Open weights
- Yes
- Best at
- Range of sizes, multilingual, open weights
- Pricing
- Open weights free; API per token
- Open weights
- Yes
- Best at
- Cited web research, real-time answers
- Pricing
- Free tier; Pro ~$20/mo; Sonar API
- Open weights
- No
- Best at
- Self-hosting, on-device, fine-tuning
- Pricing
- Open weights free; hosted APIs per token
- Open weights
- Yes
- Best at
- Microsoft 365 & Windows, work-data grounding
- Pricing
- Free tier; Pro ~$20/mo; M365 Copilot ~$30/user/mo
- Open weights
- No
- Best at
- In-editor coding: completion & agents
- Pricing
- Free tier; Pro ~$10/mo; Business per user
- Open weights
- No
Which one is right for you?
A plain decision rule for each. Most teams end up using two or three.
Pick Claude if…
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.
Read the Claude guidePick ChatGPT if…
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.
Read the ChatGPT guidePick Gemini if…
You live in Google Workspace, or you need to reason over very large documents, long videos, or mixed media in a single prompt.
Read the Gemini guidePick Grok if…
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.
Read the Grok guidePick Mistral if…
You want to self-host a capable model, care about cost-efficiency, or need a European, vendor-independent option with strong small models.
Read the Mistral guidePick DeepSeek if…
Cost is the dominant constraint and you want strong open-weight reasoning, ideally self-hosted given the data-governance questions around its hosted service.
Read the DeepSeek guidePick Qwen if…
You want open weights with a size for every job and strong multilingual coverage, self-hosted for data-sensitive work.
Read the Qwen guidePick Perplexity if…
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.
Read the Perplexity guidePick Llama if…
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.
Read the Llama guidePick Microsoft Copilot if…
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.
Read the Microsoft Copilot guidePick GitHub Copilot if…
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.
Read the GitHub Copilot guideHow to think about choosing
Start with the task. Coding and careful reasoning point one way; live information or a Google-centric workflow point another; high-volume, cost-driven, or data-sensitive work points toward open weights you can host.
Then weigh three constraints: cost (per-token API price, or compute if you self-host), data governance (where your data goes and who can see it), and ecosystem (the tools and apps you already use).
Most teams end up using two or three: a frontier model for hard problems, and a cheap or self-hosted open model for high-volume tasks.
A note on the open-weight and China-based models
Mistral, DeepSeek, and Qwen can all be downloaded and run on your own infrastructure, which is attractive for cost, latency, and keeping data in your environment.
DeepSeek and Qwen are made in China; their hosted apps and APIs run on China-based infrastructure and apply local content rules. For sensitive or regulated North-American data, prefer self-hosting their open weights over the hosted services, or use a Western provider.
Choosing an AI
common questions.
Direct answers to the questions we get asked the most. If yours isn't covered, write to the team.