LLM Opex

Models

MemT-1.0-Nano: GPU memory and hosting cost

Open weights · 35.11 billion parameters · licence apache-2.0

No cloud sells this model per token: to use it you run it yourself, on GPU instances you rent.

Run it yourself

It needs 87.8 GB of GPU memory at bf16, the precision it ships in.

CloudCheapest instance that fitsGPUsAn hourA month, around the clock
Nebiusgpu-rtx6000-a.1gpu-24vcpu-218gb1 × RTX PRO 6000 96 GB$1.80$1,314
DeepInfrah200.1x1 × H200 141 GB$3.49$2,548
Core42mi300x.1x1 × MI300X 192 GB$3.50$2,555
Google Cloudg4-standard-481 × RTX PRO 6000 96 GB$4.50$3,285
HF Endpointsaws.nvidia-h200.x11 × H200 141 GB$5.00$3,650
AzureStandard_NC144ds_xl_RTXPRO6000BSE_v61 × RTX PRO 6000 96 GB$6.38$4,657
Alibaba Cloudecs.gn8v.4xlarge1 × GPU H 96 GB$7.31$5,337
Fireworks AIh200.1x1 × H200 141 GB$8.00$5,840
IBM watsonxdeploy-on-demand.1xH2001 × H200 141 GB$16.00$11,680
Crusoea100-sxm.8x8 × A100 80 GB$18.40$13,432
AWSp4d.24xlarge8 × A100 40 GB$21.96$16,029
Together AIhgx-h100.8gpu8 × H100 80 GB$31.92$23,302
OCIBM.GPU.A100-v2.88 × A100 80 GB$32.00$23,360

More from Other

Similar size, open weights

List prices collected 4 November 2026, refreshed every three hours. No negotiated rates or taxes.