Hyperbolic Alternatives for Inference

Serving or batch-running a model for generation, where throughput per dollar decides the bill.

What inference actually needs

48 GB+
VRAM floor
Rarely
Multi-GPU
If it checkpoints
Survives losing the box
Not much
Environment persistence

Why people look past Hyperbolic for this

Little state to carry, so this is the job that moves most freely on price. The cost is the weight pull and the warm-up on the new box, not lost work. That is exactly the gap Hyperbolic does not close: Hyperbolic pairs open-model inference with rentable GPU capacity, aimed at developers who want both from one vendor. We do not host open models for you: our jobs run a version of a setup you built yourself, not a catalogue you pick a model from.

To be fair, Hyperbolic's real strength is real: Hosted open-model inference alongside GPU rental, from a single account.

Live rates for the GPUs inference wants

GPU
From (per GPU/hr)
Providers
H100
$1.99
8
H200
$3.59
6
A100
$0.668
7
L40S
$0.668
5

Live per-GPU rates from Aquanode's marketplace. Refreshes hourly.

How you run it here today

Run it today with the seeded vllm-batch job recipe — a real, publicly-imaged container Aquanode can queue directly, not a template we're promising to build later.

Restoring an environment requires a snapshot that already exists. Stopping a deployment yourself captures it on the way out, so you can bring it back later on any provider. A provider-side termination is different: it is only recoverable if you had already switched automated snapshots on for that deployment, and it costs you the work since the last one. Automated snapshots are opt-in, nothing runs until you start it, and with none running there is nothing to restore.

More alternatives pages

Inference alternatives to other clouds

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