Most chatbot vendors quietly choose your AI model for you. That is a mistake, because no single model is best for every customer question. The right approach is routing: send routine questions to a cheap, instant model and complex ones to a flagship model. Here is how the major models actually compare for customer support.
The four models, in support terms
GPT-4 class (OpenAI)
The safe default. Excellent instruction following, strong tool use, mature APIs. Best for complex troubleshooting and anywhere reliability beats cost. Downside: the most expensive per-query inference of the group.
Claude (Anthropic)
Outstanding long-context handling and nuanced, natural language. Claude shines when conversations are long - full ticket threads, large documentation chunks - where other models lose context.
Gemini (Google)
Fast, strong multimodal abilities (useful for screenshots and documents), and aggressive pricing through Google's AI Studio. A great value pick for knowledge-heavy workflows that include images.
Groq
The speed champion. Ultra-low latency inference for Llama-class open models, costing a fraction of flagship APIs. Ideal for high-volume, simple queries where a sub-second answer matters more than reasoning depth.
Latency, cost, and complexity trade-offs
- Latency - Groq leads, Gemini is fast, Claude and GPT-4 are slower but more thorough.
- Cost - Groq and open models are cheapest; GPT-4-class is priciest; Claude and Gemini sit between.
- Quality - for multi-step reasoning and emotional nuance, GPT-4 and Claude win; for short factual answers, the difference is small.
Why multi-LLM beats single-model
A customer asking "where is my refund?" does not need a flagship model. A customer describing a broken integration does. A single-model setup forces you to pay flagship prices for every question, or accept cheap-model quality for the hard ones. Multi-LLM routing solves both: your rules decide which model handles which conversation, and you switch providers whenever pricing changes.
What to look for in a platform
- Support for at least two flagship models plus a cheap-fast option.
- Per-conversation or per-rule model selection, not one global setting.
- No lock-in - bring your own keys or use provider-managed keys.
Chatonn was built around this exact idea: connect OpenAI, Claude, Gemini, and Groq in one dashboard, route conversations to the right model automatically, and watch your inference bill shrink. Start free and test all four models on your own questions today.
Put this into practice
Chatonn turns your documentation into an AI support agent that answers instantly and hands off to your team when it should.