Compute Compass Offline by design

AI HARDWARE, EXPLAINED

Start with what you want to do.

Choose your work. Set a limit. See what fits, what doesn’t, and why.

See my recommendation ↓
01

What do you want to do?

Pick as many as you need. These are common workloads, not a ranked popularity chart.

02

Your new-hardware budget

$USD
Use what I own$5 million

A ceiling, not a target. Hardware estimates exclude tax, shipping and facility work.

03

How you want it to work

This sets planning assumptions. You can inspect every memory allowance in the results.

The result tells you the facility required and estimated parallel capacity. Start with a setup that fits one instance of each selected model family under your chosen residency mode.

Model sizes & advanced options

The defaults suit smaller local models. Open this when you need larger models, original-weight precision, a team service or specialized infrastructure.

Managed service restricts new language-model hardware to professional multi-GPU workstations or servers. Facilities are an output, never a hidden filter.

Quantization reduces weight precision, not video resolution. Published original weights are not always 16-bit. More precision does not guarantee a visibly better result.

Leave experimental ports and distributed setups off for the more straightforward software path. Exact model support still needs checking.

04

What you already own

Existing devices cost $0 in the plan. Their memory stays separate.

Save your plan

Copy the text or download a file. If your embedded browser blocks downloads, use Copy or open the app in a standard browser.