01
Local first
Eligible work can begin on the user's machine before it asks for hosted headroom.
FREE TO THINK
● PRIVATE PREVIEW UTC
● INFERENCE COSTS
Stop renting
every inference.
TARX helps AI apps use local compute first and hosted Supercomputer headroom when more power is needed.
Local firstHosted headroomCost disciplineNo token wrapper
Economic pain
Cloud-only AI
gets expensive.
When every useful action starts in rented infrastructure, usage growth can become a bill before it becomes a business. TARX is designed to shift eligible work local-first and reserve hosted Supercomputer headroom for work that truly needs it.
First path
Use the compute
already in the room.
The cost argument starts with architecture. If local compute can do the job, the app should not default to a remote meter.
02
Hosted when needed
Bigger jobs can still use hosted Supercomputer headroom when local compute is not enough.
03
Clear pricing story
Paid plans should explain more hosted Supercomputer headroom, not hide the cost model behind vague usage language.
Not a wrapper
The runtime changes
the cost surface.
TARX is not a token-pricing wrapper around the same cloud-only path. The runtime chooses local-first where it can and hosted headroom where it should.
01
Architecture shift
Reducing dependency starts by changing where eligible work runs.
02
Headroom model
Hosted compute becomes extra capacity for heavier work, not the only place work can happen.
03
Enterprise path
Teams that need more control can move toward enterprise-owned runtime deployment as the contract matures.
Proof status
No savings promise.
This page explains a cost architecture. It does not promise a fixed savings percentage, name competitor prices as verified truth, or claim hosted compute disappears.
Current proof
Pricing methodology, local runtime evidence, and sourced assumptions for any modeled cost comparison.
Model note
Cost language should stay tied to architecture and sourced assumptions until live usage data is available.
FAQ
Questions
answered plainly.
How can TARX reduce inference dependency?
TARX is designed so eligible work can start on local compute instead of sending every action to hosted infrastructure.
Does TARX eliminate hosted compute?
No. Hosted Supercomputer headroom remains useful for heavier work and for workloads that local compute should not handle.
What is Supercomputer headroom?
Supercomputer headroom is hosted compute capacity available when local runtime is not enough for the job.
Are Joules the same as tokens?
No. Joules are TARX's hosted Supercomputer compute unit. The public pricing story should be explained as hosted headroom, not led by Joules.
Who is this useful for?
It is useful for builders and AI teams whose usage is growing and who want more control over where work runs.
Private preview
Start with
TARX runtime.
Tell us what you are building and where local-first execution should fit.