GPT vs Claude vs Gemini for customer support
GPT (OpenAI), Claude (Anthropic) and Gemini (Google) can all write a solid customer support draft. The differences that matter for a support team are tone habits, cost profile, how each handles prompt caching, whether it offers embeddings, and which plan unlocks it. In ReplyRabbit, all three are a mailbox setting on the Pro and Team plans, and OpenAI is the free-plan provider, so the practical answer is to run two side by side on real tickets and count edits.
The three at a glance
| GPT (OpenAI) | Claude (Anthropic) | Gemini (Google AI Studio) | |
|---|---|---|---|
| ReplyRabbit plan | Free, Pro, Team | Pro, Team | Pro, Team |
| Typical strengths | The common default; broad, dependable drafts | Careful, natural replies that stay on the question | Fast, low-cost options for volume and background tasks |
| Prompt caching in ReplyRabbit | Safe cache routing key sent automatically | Caching used automatically when reuse is likely; falls back if rejected | No forced setting; cache metadata recorded when Google returns it |
| Embeddings for semantic search | Yes | No; use another provider for the Embeddings task | Depends on your setup; test it |
| How you pay | Your OpenAI account, per token | Your Anthropic account, per token | Your Google AI Studio account, per token |
Model versions and prices change too often to print here. Check each vendor's current list before you standardise.
Tone: the difference agents notice first
With company context and response style filled in, all three follow your rules. The residual differences are habits. GPT drafts tend to be evenly structured and safe. Claude drafts often read more like a person who's read the whole thread and is answering just that. Gemini drafts, especially from the smaller models, are brisk and to the point.
None of these is better in the abstract. A team that writes warm, chatty replies will edit a brisk draft; a team that writes short, factual replies will trim a warm one. Test with your own examples loaded.
Cost: think in tasks, not models
The bill depends more on how you split tasks than on which family you choose. Drafts are the only task that needs a top model. Previews and attachment reading on the Team plan can run on the cheap default from any provider. A common pattern is Claude or GPT on Drafts, Gemini or a cheap GPT model on Mailbox previews, and OpenAI on Embeddings. Each subsection in Per-task AI models picks its own provider and reuses saved keys.
Whatever the split, set a Monthly Token Budget on the mailbox. It counts total tokens regardless of caching discounts.
Privacy: the same for all three
Each of these is a cloud provider. For an enabled feature, ReplyRabbit sends the conversation text needed for that task plus your context and style rules, and the vendor processes it under its own terms. If that's not acceptable for a mailbox, the answer isn't a different cloud vendor; it's a local Ollama or LM Studio model on that mailbox. See Choosing an AI provider.
Running the comparison
- Put GPT on one mailbox and Claude or Gemini on another, both with the same company context and examples.
- Turn on Auto Draft and work a normal week.
- Track three numbers per draft: sent with light edits, rewritten, or contained an invented fact.
- Compare provider spend for the week.
- Keep the winner on Drafts, and move cheaper tasks to the cheaper family.
Setup for each provider is in How to set up ReplyRabbit; connection guides are Connect FreeScout to OpenAI, Connect FreeScout to Anthropic Claude and Connect FreeScout to Google Gemini. For failures, see Troubleshooting ReplyRabbit and the FAQ.
Official references
Provider names, model lists, pricing, privacy terms, and legal guidance change. Check the current source before setting a production policy.