LLM API cost calculator
Plug in your monthly token volume, pick your workload (RAG, chatbot, agent loop, summarization, code-gen), and see exact monthly cost across 19+ models — with workload-specific recommendations.
LLM API costs scale linearly with token volume, but the right model for your workload depends on three axes: intelligence, speed, and price. Picking the cheapest model can mean paying for outputs that don't meet quality thresholds; picking the most expensive can mean burning budget on tasks a smaller model would have solved.
The Qaynaq Labs LLM Cost Calculator combines deterministic pricing math with workload-aware recommendations across 19+ models from Anthropic, OpenAI, Mistral, Google, Meta (via Groq), Cohere, DeepSeek, and xAI. Plug in your monthly token volume, pick your workload, and see exact monthly cost plus alternatives ranked by total spend. The recommendation engine considers your scenario — RAG is input-heavy, agent loops are output-heavy — and suggests the model that hits the right intelligence-cost trade-off.
Frequently asked
How current is the pricing?
Pricing is updated regularly against vendor pricing pages. We list the date the table was last verified and link to the vendor's official pricing for confirmation.
Does it account for prompt caching?
Recommendations call out when prompt caching (Anthropic, OpenAI, Mistral) would dramatically change the math for your workload. The base calculation assumes no cache for transparency.
What's the difference between batch and live API pricing?
Most providers offer ~50% discount for batch API. The recommendation section flags when batch is appropriate for your workload.
Do you cover open-source self-hosted models?
We list managed providers (Groq, Together, Fireworks) for Llama. Pure self-hosted cost depends on your GPU spend, which is outside the calculator's scope.