Reserve the hardware, not a place in the queue.
Ascend NPUs held for your organisation alone, in country, billed for the time you hold them rather than the tokens you send.
Two meters, and the cheaper one depends on your traffic.
A meter that rewards volume
Shared capacity bills per million tokens, so cost tracks usage exactly and idle costs nothing. Reserved capacity bills for held time, so every extra token you push through the same NPU is cheaper than the last. There is a crossover, and it is the whole conversation.
Latency you own
No shared queue means no neighbour's batch landing in front of yours. Throughput and tail latency stop being a function of what everyone else on the platform is doing this minute.
Sovereign by construction
The NPUs are racked in Pakistan and so are the logs and the billing records. Residency is a property of where the hardware sits, not a checkbox in a console, and it does not change when you reserve some of it.
- 01
Steady, heavy traffic
Sustained load rather than spikes. A reservation you use a few hours a day is more expensive than paying per token for those hours.
- 02
A latency floor to hold
A number you have committed to someone else, that a shared queue cannot be made to guarantee.
- 03
Model pinning
Specific weights that must stay resident, including models outside the shared catalogue.
If none of those describe you, shared capacity is the cheaper answer and we will say so. Reserved hardware you do not keep busy is the most expensive way to buy inference.
Tell us what you want to run, and we will size it.
Reservations are quoted per organisation, because the price depends on which weights stay resident and how much of a cluster they hold. We will come back with a configuration and a rupee figure, and with the per-token comparison, so you can see which meter is actually cheaper for your traffic.
Looking for an engineer rather than hardware? Talk to our engineers instead. Prefer email? Write to info@intelligentinference.ai.