Cloud-Native Model Quantization
for Efficient Inference
Compress your models with production-ready precision—lower costs, smaller memory footprint.
Why Quantization Matters
Cut Inference Costs by Up to 60%
Quantization with INT4 or NVFP4 significantly reduces compute overhead, helping lower inference costs by up to 50–60% on average—without changing your model architecture.
Reduce VRAM Usage by Up to 75%
Lower-precision weights dramatically shrink memory requirements, reducing GPU VRAM usage by up to 70–75%, enabling higher throughput and better hardware utilization.
Run Larger Models on Smaller GPUs
Quantized models can run efficiently on smaller or more affordable GPUs—making it possible to deploy large-scale models without high-end hardware.
Simple & Cloud-Native Workflow
01
Zero Local Setup, Fully Cloud-Native
Start quantization directly in the cloud—no local environment, no CUDA setup, and no dependency management required.
02
Automated Quantization with Efficient Turnaround
Most quantization jobs complete within a predictable timeframe, depending on model size and precision—fully automated from start to finish.
03
Quantize from a Hugging Face Model URL
Simply provide your Hugging Face model URL, select the target precision, and launch the quantization task in minutes.
04
Support for INT4 and NVFP4 Precision
Choose between industry-standard INT4 or next-generation NVFP4 to balance inference efficiency and model quality.