Input vs output token spend
Output tokens usually cost several times more than input, so answer length is what really drives your bill.
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AI & LLM Cost
LLM Cost Calculator
Estimate the running cost of any large language model. Set your monthly volume and token sizes, choose a model, and this LLM cost calculator returns the monthly bill with a full 2026 price comparison across providers.
Estimated monthly cost
$0
Cost per request—
Cost per 1,000 requests—
Input token cost—
Output token cost—
Tokens processed / month—
Annual estimate—
The same workload priced across AI models
Your monthly token volume run through popular 2026 models, cheapest first.
What the LLM Cost Calculator does
A large language model is billed by usage, not by seat, so two teams running the same model can pay wildly different amounts. What matters is how many requests you make and how many tokens each one moves. This LLM cost calculator captures both and turns them into a monthly and annual figure.
Because model choice can swing the total by ten times or more, the tool prices your exact workload against the most used 2026 models at once. That makes it easy to spot when a smaller or open model would carry the same load for a fraction of the price.
Heads up on pricing. The rates built into this tool are public list estimates for July 2026 and can change without notice. Providers also offer batch discounts, prompt caching and volume tiers that lower real costs, so treat the output as a planning estimate, not a quote.
The formula
tokens per month = requests × (input tokens + output tokens)
cost = (monthly input ÷ 1M × input rate) + (monthly output ÷ 1M × output rate)
cost = (monthly input ÷ 1M × input rate) + (monthly output ÷ 1M × output rate)
Worked example
A support assistant handles 250,000 requests a month at 1,500 input and 350 output tokens each. On Gemini 2.5 Flash that is 375M input × $0.30 + 87.5M output × $2.50 per million = $112.50 + $218.75 = about $331 a month. The same traffic on GPT-5 would be closer to $1,344.
AI model pricing used in this calculator (July 2026 estimates)
| Model | Provider | Input / 1M tokens | Output / 1M tokens |
|---|---|---|---|
| GPT-5 | OpenAI | $1.25 | $10.00 |
| GPT-5 mini | OpenAI | $0.25 | $2.00 |
| Claude Opus 4.1 | Anthropic | $15.00 | $75.00 |
| Claude Sonnet 4.5 | Anthropic | $3.00 | $15.00 |
| Claude Haiku 4.5 | Anthropic | $1.00 | $5.00 |
| Gemini 2.5 Pro | $1.25 | $10.00 | |
| Gemini 2.5 Flash | $0.30 | $2.50 | |
| DeepSeek V3 | DeepSeek | $0.27 | $1.10 |
| Grok 4 | xAI | $3.00 | $15.00 |
| Llama 4 Maverick | Meta | $0.20 | $0.60 |
Prices are public list estimates for planning as of July 2026 and change often. Providers bill per token, where roughly 1,000 tokens equals about 750 words. Always confirm live rates on the provider pricing page before you set a budget.
Ways to lower your AI costs
- Match the model to the task. Route simple requests to a small model like GPT-5 mini, Gemini Flash or DeepSeek V3, and keep premium models for complex reasoning where quality pays off.
- Cache repeated context. Prompt caching means you stop paying full price for the same system prompt or documents on every call.
- Cap output length. Output tokens cost several times more than input, so limiting response length is often the fastest saving you can make.
- Trim prompts and history. Summarize old conversation turns and drop context the model does not actually need to answer well.
- Batch non-urgent work. Many providers offer batch pricing at around half the standard rate for jobs that can wait a few hours.
Frequently asked questions
What drives LLM cost the most?
Three things: the model you pick, how many tokens each request uses, and how many requests you send. Output length and attached context are the usual culprits behind a surprise bill.
Is a cheaper model always worse?
Not for every task. Smaller models like GPT-5 mini, Gemini Flash or DeepSeek V3 handle classification, extraction and routine chat well, so reserve premium models for the hard requests.
How do I estimate tokens if I do not know them?
Start with 1,000 input and 500 output tokens as a rough default for a chat turn, then refine using your provider tokenizer once you have real prompts.
Does context length pricing apply?
Some models charge a higher rate above a context threshold, such as very long inputs. For most everyday workloads the standard rate in this tool is what applies.
Are these figures a quote?
No, they are July 2026 planning estimates. Batch discounts and caching can lower real costs, so confirm with the provider.