USE-CASE GUIDES

Best LLM API for chatbots & customer support

Conversational traffic is high-volume and response-heavy, so the output rate matters more than usual. These are budget-tier models sorted by output price, cheapest first.

Customer-support chatbots typically run at high volume with relatively short, templated responses, which makes the output price — what you pay per reply generated — the number to watch. This list filters to our budget-tier models and sorts by output price ascending.

ℹ️How this list is built: Filtered to the budget tier, sorted by output price ascending.
11 models
Model Provider Input /1M Output /1M Context
Meta (via Together AI) $0.18 $0.59 1M tokens
Mistral $0.15 $0.60 Not published
Meta (via Together AI) $0.27 $0.85 ~1.05M tokens
OpenAI $0.20 $1.20 ~1.05M tokens
DeepSeek $0.30 $1.20 1M tokens
Google $0.25 $1.50 Not published
Mistral $0.50 $1.50 Not published
Alibaba $0.40 $1.60 1M tokens
xAI $1.00 $2.00 256K tokens
Amazon $0.30 $2.50 1M tokens
Anthropic $1.00 $5.00 200K tokens

We don't benchmark task-specific quality — this shortlist is built from verified price and published context window only. Use it to narrow candidates by cost, then evaluate output quality yourself.

See all use cases →

Frequently asked questions

Support conversations tend to have a moderate prompt, but the bot's replies are what repeats at volume across thousands of conversations — so the cost of generating those replies is usually the bigger lever on your total bill.

For a large share of support volume — order status, FAQ-style questions, simple troubleshooting — yes, that's the case many teams make. For complex or sensitive conversations, escalating to a stronger model (or a human) is the more common pattern.

Then check the context window column too, not just price — a long knowledge base fed into every prompt adds up on the input side even if replies stay short. Our long-context list is the better starting point if that's your main constraint.