Use your GPU.
Pay nothing per generation.
Run the AXIS Foundry worker on your own machine. Generate as many 3D models as you can compute — text-to-3D, image-to-3D, mesh repair, rigging — all unlimited, all local. One flat subscription. No per-mesh metering.
Step 1 · Your hardware
Live capability check
We probe your browser for GPU adapter info. This is a fast
first-pass eligibility signal — the real authority is the
worker, which inspects nvidia-smi /
system_profiler / wmic at registration time.
Minimum: 8 GB VRAM · Recommended: 16 GB · Best: 24 GB+ (RTX 4090 / 3090 / A6000). Integrated Intel iris/HD/UHD and AMD Vega 8/10 are not eligible — too little VRAM to keep generation under our 60-second SLO.
Step 2 · Why creators run their own GPU
Stop paying per mesh
| What it costs | Cloud GPU plan | BYOGPU Unlimited |
|---|---|---|
| Monthly base | $59 / mo (Studio) | $100 / mo |
| Generations per month | ~450 included, then $0.13 each | UNLIMITED |
| Cost of 1,000 generations | ~$130 over plan | $0 over plan |
| Cost of 10,000 generations | ~$1,300 over plan | $0 over plan |
| Generation latency | 30–90s (queued) | 10–40s (your hardware) |
| Prompt + IP privacy | Sent to our cloud GPU | Never leaves your machine |
| Offline use | Requires internet | Cache locally, generate offline |
Per-mesh cost on cloud plans is the published list price. Your actual ROI depends on volume — BYOGPU breaks even around 770 generations / mo and is pure savings beyond that. Heavy users save thousands per month.
What you get
A real production worker — not a demo
Unlimited everything
Text→3D, image→3D, parametric avatars, mesh repair, auto-rig. No per-action metering. Burn through 10,000 generations a month if you want.
Stdlib-only scaffold
The downloadable worker is pure Python 3.11 stdlib — no requests, no numpy. It dispatches to your local torch/diffusers, which you install once.
Deterministic & signed
Same seed → same mesh. SHA-256 provenance chain. HMAC-signed manifests. The worker package itself is deterministic — same input, byte-identical ZIP.
Auto-pair to your account
One-time 15-minute pairing code. The worker registers, gets a long-lived token, and starts heartbeating. Revoke any worker from the console.
Multi-machine
Pair as many workers as you own — workstation, laptop, that crypto-mining rig you don't use anymore. They all draw from the same unlimited subscription.
Cancel anytime
No annual lock-in. No setup fee. Subscribe in November, ship a game in December, cancel in January. Your provenance manifests stay valid forever.
Step 3 · How it works
Four commands. Then it just runs.
-
Activate BYOGPU on your account
Subscribe above. Your portal account flips to plan
byogpuwith unlimited generation rights. -
Download the worker package
A 5 KB stdlib-only ZIP. Drop it anywhere. It only needs Python 3.11+.
You install
torch,diffusers, and the model weights ONCE — exactly the dependencies you'd install for any local diffusion setup. -
Generate a pairing code in the Console
One-shot, expires in 15 minutes.
POST /portal/api/byogpu/workers/pairreturns the code and an exact install command. -
Run it
python -m axis_foundry_worker pair --code <CODE> --label "Workstation", thenpython -m axis_foundry_worker run. The worker heartbeats every 30s. Studio jobs route to it automatically.
Step 4 · The download
axis-foundry-worker — stdlib-only scaffold
The download is public so you can inspect it before subscribing. Pairing (and therefore actually doing work) requires an active subscription.
Step 5 · Questions creators ask
Honest answers
Is the worker really stdlib-only?
The scaffold is. It uses urllib for HTTP, subprocess for GPU detection, zipfile + json. To actually generate, you install your favourite diffusion stack (torch + diffusers + a t23 / image-to-3D model). The worker dispatches to whatever you have installed — we don't lock you to one model.
What if my GPU is too small?
The hardware probe will flag you ineligible (under 8 GB VRAM or a known underpowered chip). You can still subscribe and run on a different machine, but we won't let an obviously underpowered worker pair — it would just frustrate you with timeouts.
Where does my data go?
Prompts and images stay on your machine. The portal only sees: worker heartbeats (status + last_seen timestamp), job IDs, and the final asset manifest (which lives in your storage anyway because you initiated the job). Nothing about the generation itself.
Can I cancel?
Yes. From Billing → Switch back to a free or paid token-pack plan. Your existing generations and manifests stay valid forever — the provenance chain doesn't depend on subscription state.
Does this work behind a corporate firewall?
The worker only needs outbound HTTPS to the AXIS API. No inbound ports. Standard corporate egress allows it.
What counts as a "generation"?
Anything that would normally consume tokens — text-to-3D, image-to-3D, parametric, mesh repair, auto-rig, validation+export. On BYOGPU, none of it is metered.