Cost to Process 1,000 Support Tickets with LLM APIs
Calculate the real cost of using LLM APIs to handle customer support tickets. Compare all models side-by-side for processing 1,000 support tickets with verified per-million-token pricing.
⚡ Your Workload
📊 Cost Summary
Cost per support tickets across 153 models
Show all 153 models in a table
| Model | Provider | Input $/M | Output $/M | Cost for 1K support tickets |
|---|
How this calculator works
Each support ticket typically requires ~1,500 input tokens (system prompt, conversation history, knowledge base context, customer message) and ~400 output tokens (the AI response). This estimate assumes a RAG-enhanced support agent that retrieves relevant documentation before responding. Actual token usage varies by ticket complexity, context window size, and whether multi-turn conversations are needed.
Formula: cost = (input_tokens × input_price_per_Mtok + output_tokens × output_price_per_Mtok) × quantity / 1,000,000
All prices are per million tokens, sourced directly from official provider pricing pages and verified by our automated scraper pipeline that runs 3× daily. No fabricated numbers — every price links to its source.
Frequently asked questions
How much does it cost to process 1,000 support tickets with an LLM API?
The cost depends on the model you choose. Using a budget model like DeepSeek V3, 1,000 support tickets costs approximately $1-3 per month. Using GPT-4.1, it costs around $15-30. Using a frontier model like Claude Opus 4.8, it can cost $50-100+. See the calculator above for exact numbers across all models.
Which LLM API is cheapest for customer support automation?
The cheapest viable models for support ticket automation are typically DeepSeek V3, Google Gemini Flash, and Groq-hosted Llama models. These cost under $1 per 1,000 tickets while maintaining reasonable response quality for standard support queries.
How are support ticket token costs calculated?
Each ticket uses ~1,500 input tokens (context + customer message) and ~400 output tokens (AI response). Total cost = (input_tokens × input_price_per_Mtok + output_tokens × output_price_per_Mtok) × number_of_tickets. All prices are per million tokens, sourced from official provider pricing pages.