Reduce VRAM memory requirements by up to 45% without sacrificing model accuracy. Designed for high-end inference clusters and production scale.
Built on top of the H2O algorithm, Nesion manages your GPU memory so you can run larger models on existing hardware.
Engineered in low-level PyTorch kernels to ensure zero impact on total inference token-per-second metrics.
Minimal configuration required. Integrates with existing Transformers and VLLM pipelines in a single line of code.
Tested on massive token batches to ensure stability and deterministic output quality.
Works with every major open-source architecture. One integration. Zero architectural changes.
+ Phi, Falcon, Cohere, StarCoder, OLMo, StableLM, InternLM, DBRX, Arctic, Grok, and more.
Transparent pricing designed for researchers and enterprise teams alike.
For teams running ≥2 GPUs in production.
$49/GPU/moNo credit card required. Cancel anytime.