Free Tool

LLM API Cost Calculator

Pick any model, enter your expected token usage and daily call volume, and instantly see your projected costs — per call, daily, monthly, and yearly. Compare with cheaper alternatives below.

1. Configure Your Usage

Select the LLM model you're using or evaluating
Your prompt size (1 token ≈ 4 characters)
Expected response length
Total requests across your application
Business days or calendar days
$0.00
Per Call
$0.00
Daily
$0.00
Monthly
$0.00
Yearly

2. Cost Breakdown

Component Tokens Rate (per 1M) Cost / Call
Input tokens 1,000 $0.00 $0.00
Output tokens 500 $0.00 $0.00
Total 1,500 $0.00

3. Cheaper Alternatives

Models that can do the same job for less, sorted by savings.

Model Provider Cost / Month Savings

Related Free Tools

Calculate costs here, then count tokens or compress prompts to save more.

🔢 Token Counter
Paste text and see the exact token count across GPT-4o, Claude, DeepSeek, and more.
⚡ Prompt Optimizer
Compress your prompts to reduce token usage by 10-40% — savings calculated instantly.

Stop estimating. Start measuring.

This calculator estimates costs. Tokonomics tracks your real API spend per call, per feature, per team — with hard caps that prevent overruns.

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Frequently Asked Questions

How accurate is this LLM cost calculator?

This calculator uses official pricing from each provider as of June 2026. Actual costs may vary based on prompt caching discounts (up to 90% off with Anthropic), batch API pricing (50% off with OpenAI), and volume commitments. The estimates assume standard on-demand pricing with no discounts.

How do I estimate input and output tokens?

A rough rule: 1 token ≈ 4 English characters or ¾ of a word. A 500-word prompt is roughly 375 tokens. For precise counts, use our token counter tool. Output tokens depend on your use case: classification might produce 10 tokens, while content generation could produce 2,000+.

What's the cheapest LLM API for production use?

For text tasks (classification, summarization, Q&A), DeepSeek V4-Flash and Gemini 2.0 Flash offer the lowest per-token pricing. GPT-4o-mini and Claude Haiku 4.5 are strong mid-range options. The cheapest model depends on your quality requirements — see our cheapest LLM per use case guide.

How can I reduce my LLM API costs?

Five proven strategies: (1) enable prompt caching for repeated instructions, (2) use smaller models for simple tasks, (3) compress prompts to reduce input tokens, (4) batch requests when latency isn't critical, (5) set hard budget caps to prevent runaway spending. Read our cost optimization guide for implementation details.