
Powering CUDA AI in Omarchy.
TensorFold powers Omarchy’s NVIDIA model recipes, including DGX Spark, N1x and paired Sparks.
Explore Omarchy local AI
Run open models on the GPUs you own, with native Metal and CUDA inference.
App 1.0.0 · Engine 1.2.0 · Apple silicon · macOS 13.3+
curl -fsSL https://tensorfold.dev/install.sh | shChoose a local model, start its server and connect the tools you use.
See how it works
Models running with TensorFold

TensorFold powers Omarchy’s NVIDIA model recipes, including DGX Spark, N1x and paired Sparks.
Explore Omarchy local AIAn experimental TensorFold integration for ComfyUI’s creative workflows. Contribution in progress.
Follow the contributionReal runs on named hardware.
Open the release. Inspect the conditions.
RTX PRO 6000 Blackwell
Greedy code decode with drafting enabled, an MLX affine 4-bit checkpoint and the CUDA engine.
Each number is its own release measurement, on the model and machine named under it: not a like-for-like comparison.
Community benchmarksDrafted tokens. Reused prompts. Connected machines.
On supported models, a drafter proposes several tokens and the target checks them together, committing only the matching prefix.
Free, open-source AI infrastructure for enterprise fleets. Share Macs and GPU servers with company sign-in, model deployments and project budgets. All improvements land on GitHub.
Deploy and manage it yourself for free, without direct support. For deployment help or long-term support, back the project through donations or sponsorship and agree a support scope with us.
Discuss backing & support
Compare community runs on named hardware, inspect the receipts and share your results.
Explore the leaderboardPart of NVIDIA's startup program.
With thanks to Mia and her team for their patches, setup and testing.
Explore the collaboration ↗
Deployment in preparation.
A satellite deployment is in preparation. Hardware results will follow qualification.
Concept illustration.