Built for the card you have

Most local audiobook tools quietly assume you already have the graphics card they were built on. Castwright is built the other way round — for the card you actually own.

It runs on a 6 GB card. The default English path — Kokoro voices, with analysis in the cloud or on a small local model — fits comfortably on 6 GB. The heavier designed-voice work is tighter there but still runs; 8 GB is the sweet spot, where designed voices and the Higher-quality tier have room to breathe. Have 12 or 16 GB? Analysis and voices stay loaded together and run at the same time.

The trick is that the two halves take turns. Reading a book (working out who says what) and performing it (the voices) are separate jobs. On a smaller card, Castwright doesn’t try to hold both at once — the analyzer steps aside before speech, so their memory never has to add up. Run the analysis in the cloud or on your CPU and it uses no graphics memory at all, leaving the whole card for voices. That’s why a 6 GB card can carry the whole pipeline.

Two cards, both working. If you have more than one graphics card, place each voice engine on the card you choose — and each card is watched on its own. A job that’s genuinely too big for a card settles into a clean, safe stop instead of struggling in the background.

It stops cleanly, not catastrophically. Running close to a card’s limit is where local tools usually fall over. Castwright budgets its graphics memory deliberately and protects every path, so when a card is asked for more than it has, you get a clear stop — not a crash, not a silent slowdown you only notice an hour later.

There’s a full breakdown of which voice engine and which analysis model fit on 6, 8, and 12–16 GB cards on the system requirements page.

Two more expressive engines are on the way for bigger cards — one aimed at 12 GB, one at the 16 GB tier — as that support matures. But the promise holds at the entry point too: the card you already have is enough.

Many voices, one machine.