Macola AI Assistant Sizing and Value Calculator
This free calculator estimates GPU count, token volume, document index size, hours saved and payback for a private AI assistant on Macola. Change the inputs to match your user base and see the chart for how cost and value scale with users.
Your numbers
Licensed or named Macola users who could use the assistant.
Percent of named users who ask at least one question per day.
Include retrieved context. Typical range 1000 to 3000.
Measure in a pilot; this is the most uncertain input.
Amortised purchase plus power, space and support, or a private cloud rate.
Assumption: depends on model, quantisation and batching. Measure on your hardware.
Integration, indexing, testing and rollout effort.
Your results
Planning estimate. Throughput, minutes saved and token counts vary widely; measure them in a pilot before committing budget.
Monthly value vs GPU cost by named users
Sweeps Named users from 10 to 1000, holding your other inputs fixed.
Optional Macola pilot sizing
We can help turn these estimates into a measured pilot on your Macola data.
Optional. The tool and every export work without this. No spam.
How to use the calculator
Enter named Macola users and the share who actually use the assistant on a typical day, then how many questions each asks and how many tokens a question and answer consume together. Add the number and length of documents you plan to index, the minutes each answer saves and your loaded hourly cost. The outputs give peak concurrent requests, a GPU estimate with and without a standby, the index size and a simple monthly value.
Formulas and assumptions
Questions per day are active users times questions each. The busiest hour is assumed to carry 25 percent of daily questions and each answer to take 20 seconds, which sets peak concurrency. Load in tokens per second is the larger of concurrency times 40 tokens per second per stream and busy-hour tokens divided by 3600. GPUs needed are the larger of the GPUs required to hold the model and load divided by the throughput per GPU you enter. Index size assumes 2 chunks per page and about 6 KB per chunk including vectors and metadata. A month is 21 working days.
Reading the result
For a Macola-sized user base the GPU count is usually driven by the model's memory footprint, not by user load, so the estimate often lands at one or two cards. Value depends almost entirely on minutes saved per question, which is the number to test with a pilot. If payback shows zero, the monthly value does not cover the monthly GPU cost under your inputs.
Frequently Asked Questions
Why is the GPU count so low?
A few dozen active users generate light load. The count is usually set by how many GPUs are needed to hold the model, so a single card or a pair is common. Larger models or many more users change this.
What throughput per GPU should I enter?
It depends on model, quantisation and batching. A figure from 800 to 2500 aggregate tokens per second is a plausible range for mid-size models, but measure on your own hardware before committing.
How reliable is minutes saved?
It is the least certain input. Use a small pilot to time how long a lookup takes today versus with the assistant, then enter the measured average.
Does it include setup costs?
Payback uses the one-time setup cost you enter, divided by monthly value minus GPU running cost. It excludes licences you may already own and staff time beyond what you include in setup.
If you want these numbers tested against your real Macola usage, Netray can help run a small pilot. The calculator is free either way.
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