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LLM API Cost Calculator
What does your AI actually cost? Answer a few questions and we'll size your monthly bill across Claude, GPT, Gemini, DeepSeek, and Kimi, and show what it costs with Coworker.
A few questions first
How many people use AI?
How many AI tasks does each run per day?
What does a typical task look like?
Bigger tasks send and generate more tokens.
Which model do you default to?
The model teams reach for when unsure.
Here's your estimate
Estimates use published per-token API pricing (June 2026) and typical token sizes per task. Actual cost varies with caching, batching, and context length.
The same workload, priced across every model
Your 4,400 tasks/mo at the “standard work” size, billed on each model. This spread is exactly why routing beats picking one model for everything.
2026 pricing data
What teams actually pay for LLM APIs in 2026
We compiled current per-token API pricing across the major providers (Anthropic, OpenAI, Google, DeepSeek, Moonshot) in June 2026. Three patterns drive almost every LLM bill.
gap between the cheapest and most expensive model per input token ($0.10 vs $5.00 per 1M).
more expensive output tokens are than input, on every major provider. Verbose answers dominate the bill.
of spend is recoverable by routing each task to the right tier instead of defaulting to one frontier model.
| Model | Tier | Input / 1M | Output / 1M |
|---|---|---|---|
| GPT-5.5 | Frontier | $5.00 | $30.00 |
| Claude Opus 4.8 | Frontier | $5.00 | $25.00 |
| GPT-5.4 | High | $2.50 | $15.00 |
| Claude Sonnet | Mid | $3.00 | $15.00 |
| Gemini 2.5 Flash | Budget | $0.15 | $1.25 |
| DeepSeek V3 | Budget | ~$0.14 | ~$0.28 |
| GPT-4.1 Nano | Floor | ~$0.10 | ~$0.40 |
List prices per 1M tokens, verified June 2026 from official provider API documentation (OpenAI, Anthropic, Google). Frontier output ($30/1M) runs 24x Gemini Flash and ~75x budget open-source output.
The takeaways
- Frontier is a premium you rarely need. Flagship reasoning models (GPT-5.5, Claude Opus 4.8) run $5 input and $25 to $30 output per 1M tokens. Budget models (GPT-4.1 Nano, Gemini 3.1 Flash-Lite, DeepSeek) run $0.10 to $0.55 input and $0.40 to $2.19 output for the same token count.
- Output is where the money goes. Because output costs 5 to 8x input, the models you pick for long, generative tasks matter far more than the ones you use for short lookups.
- Routing beats picking one model. Most teams default to a single frontier model when unsure, so a one-line summary gets billed at the same premium rate as a multi-step analysis. Matching each task to the cheapest model that does it well is the single biggest lever, and it is exactly what Coworker AI does automatically.
Methodology: per-token rates compiled from published provider API documentation, June 2026. Figures are list prices; effective cost varies with caching, batching, and context length. Use the calculator above to model your own usage.
Frequently asked questions
How is LLM API cost calculated?
API pricing is per token, split into input (what you send) and output (what the model writes back). Monthly cost is your input tokens times the input rate plus your output tokens times the output rate, priced per million tokens. Output is usually 5 to 8 times more expensive than input.
Which LLM API is cheapest?
Budget models like GPT-4.1 Nano, Gemini 3.1 Flash-Lite, and DeepSeek run a fraction of frontier prices, while flagship reasoning models like GPT-5.5 and Claude Opus cost the most. The cheapest model that still does the job well is what matters, which is why routing beats picking one model for everything.
How much can model routing save?
A lot. Most teams default to a frontier model when unsure, so simple tasks get billed at premium rates. Routing each task to the right tier, a fast model for summaries and a frontier model only for hard reasoning, commonly cuts total spend by 80% or more with little quality loss.
How much does the GPT-5.5 or Claude Opus API cost?
As of June 2026, GPT-5.5 is $5 per million input tokens and $30 per million output tokens, and Claude Opus 4.8 is $5 input and $25 output. These flagship reasoning models sit at the top of the price range, and most everyday tasks do not need them.
Is DeepSeek or Gemini cheaper than GPT and Claude?
Much cheaper. DeepSeek runs about $0.27 to $0.55 per million input tokens and Gemini 3 Flash about $0.50, versus $5 for GPT-5.5 or Claude Opus. For summaries, classification, and high-volume tasks the quality gap is small, so routing those to a budget model is where most of the savings come from.
How does Coworker make AI cheaper?
Coworker AI pairs every task with the right model and the right context automatically, so you get frontier-quality chat, cowork, and code for roughly 80% less than frontier API rates. It connects to 50+ tools, is US-hosted, and is SOC 2 Type II compliant. Plans are a free trial, Pro at $29.99, Max at $149.99, and custom Enterprise.
Are these prices up to date?
Prices were verified in June 2026 from published provider API documentation. Model pricing changes often, so check each provider's pricing page for the exact current rate before committing to a budget.
Keep exploring
Stop overpaying for frontier tokens
Coworker pairs every task with the right model and context, so you get frontier-quality chat, cowork, and code for 80% less.