.webp)
L4
Energy-efficient data center GPU based on Ada Lovelace architecture with 24GB GDDR6 memory and 7,424 CUDA cores for AI inference, video processing, and edge computing applications.
GPU Benchmarks
L4 vs L40
Compare performance across LLMs and image models to find the best GPU for your workload.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
LLM inference benchmarks.
Benchmarks were run using vLLM in May 2025 with Runpod GPUs
.webp)
L40
High-performance data center GPU with 48 GB GDDR6 memory and Ada Lovelace architecture, designed for AI inference, 3D rendering, and virtualization workloads with 300W power consumption in a dual-slot form factor.
H100 PCIe
High-efficiency LLM processing at 90.98 tok/s.
Image generation benchmarks.
Benchmarks were run using Hugging Face Diffusers in May 2025 on Runpod GPUs.
H100 SXM
Unmatched image gen speed with 49.9 images per minute.
L40
AI image processing at 40.3 images per minute.
H100 PCIe
Pro-grade performance with 36 images per minute.
Case Studies
Real-world GPU performance in action.
See how teams optimize cost and performance with the right GPU for their workloads.
"Runpod has changed the way we ship because we no longer have to wonder if we have access to GPUs. We've saved probably 90% on our infrastructure bill, mainly because we can use bursty compute whenever we need it."
"Runpod has allowed the team to focus more on the features that are core to our product and that are within our skill set, rather than spending time focusing on infrastructure, which can sometimes be a bit of a distraction.”
"Runpod helped us scale the part of our platform that drives creation. That’s what fuels the rest—image generation, sharing, remixing. It starts with training."
"Runpod allowed us to reliably handle scaling from zero to over 1,000 requests per second in our live application."
"Runpod has allowed us to focus entirely on growth and product development without us having to worry about the GPU infrastructure at all."
"We could stop worrying about infrastructure and go back to building. That’s the real win.”
“The main value proposition for us was the flexibility Runpod offered. We were able to scale up effortlessly to meet the demand at launch.”
"After migration, we were able to cut down our server costs from thousands of dollars per day to only hundreds."
Runpod’s scalable GPU infrastructure gave us the flexibility we needed to match customer traffic and model complexity—without overpaying for idle resources.
