Mid-tier GPUs balance price and capability for production inference, moderate training, and professional workloads. This tier includes popular consumer cards (RTX 3080, RTX 4070) and datacenter options (A10G, A30). VRAM ranges from 8–64 GB. They're commonly used for serving ML models in production and fine-tuning with parameter-efficient methods.
| Provider | Price / hr |
|---|---|
$0.050/hr 1× | |
$0.160/hr 1× | |
$0.165/hr 2× | |
$0.250/hr 1× | |
$0.440/hr 8× | |
$0.561/hr 2× | |
$0.760/hr 1× | |
$1.56/hr 1× | |
$0.160/hr 1× |
Showing 9 of 120 price points. Visit individual GPU pages above for full pricing.
Mid-tier GPUs handle production inference for models up to 13B parameters, fine-tuning with LoRA/QLoRA, batch processing, image generation, and video encoding. They offer a practical balance between cost and throughput.
Mid-tier GPUs have lower memory bandwidth and fewer tensor cores, so throughput per GPU is lower. However, they can be more cost-effective for workloads that don't need the full power of high-tier cards. Compare pricing per token of output above.