Waitlist open

Cheaper tokens off
popular models

Access the most popular open and closed models at significantly reduced costs—powered by optimized GPU pooling and intelligent workload orchestration.


Do you realize that...

Average GPU utilization is around 10–30%; many models only take 20% of the whole GPU, and most of the GPU is wasted

10–30%
Average GPU utilization across most AI workloads
~20%
Typical model footprint on a GPU
−30%
Our savings by pooling that wasted capacity

Model Training & Fine-tuning

More workloads,
same hardware

By intelligently packing multiple models onto the same GPU, we maximize utilization—so you get more compute for less money with zero compromise on latency.

Without inference.ai
Model A
Wasted
22%
With inference.ai
Model A
Model B
Model C
Model D
Redundancy
100%

Hardware

Our GPUs

Enterprise-grade accelerators from the world's leading silicon vendors.

NVIDIA AMD
New
NVIDIA
B300
B300
Blackwell

Memory192 GB HBM3e
Bandwidth8 TB/s
TDP1000 W
NVIDIA
H200
H200
Hopper

Memory141 GB HBM3e
Bandwidth4.8 TB/s
TDP700 W
NVIDIA
H100
H100
Hopper

Memory80 GB HBM3
Bandwidth3.35 TB/s
TDP700 W
AMD
XCD XCD XCD XCD
MI355X
CDNA 4

Memory288 GB HBM3e
Bandwidth8 TB/s
TDP500 W

Proven Results

Real savings.
Real impact.

Our GPU pooling technology has already delivered measurable cost reductions and utilization improvements for teams of every size.

0k+
Optimized GPU hours
Across all workloads
↑ +30% utilization
$0M+
Cost saved for customers
vs. direct pricing
↓ Avg 30% cheaper

Get in touch

Ready to cut your
inference costs?

Drop us a line and we'll walk you through how inference.ai can reduce your model-serving spend by 30% or more.

Contact us hello@inference.ai