H200 SXM
High-performance data center GPU based on Hopper architecture with 141GB HBM3e memory and 4.8TB/s bandwidth for accelerating generative AI and HPC workloads.
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B200
Next-generation data center GPU based on Blackwell architecture that features 192GB of HBM3e memory with 8TB/s bandwidth, delivering up to 20 petaFLOPS of FP4 AI compute performance.
RTX 5090
Consumer GPU based on Blackwell architecture with 32GB GDDR7 memory and 21,760 CUDA cores for AI workloads, machine learning, and image generation tasks.
RTX A6000
Professional workstation GPU based on Ampere architecture with 48GB GDDR6 memory and 10,752 CUDA cores for 3D rendering, AI workloads, and professional visualization applications.
RTX 6000 Ada
Professional workstation GPU based on Ada Lovelace architecture with 48GB GDDR6 memory and 18,176 CUDA cores for advanced AI workloads.
RTX A5000
Professional workstation GPU based on Ampere architecture with 24GB GDDR6 memory and 8,192 CUDA cores for balanced performance in AI workloads.
RTX A4000
Professional single-slot GPU based on Ampere architecture with 16GB GDDR6 memory and 6,144 CUDA cores for AI workloads, machine learning, and compact workstation builds.
RTX 4090
High-end consumer GPU based on Ada Lovelace architecture with 24GB GDDR6X memory and 16,384 CUDA cores for AI workloads, machine learning, and image generation tasks.
RTX 3090
High-end consumer GPU based on Ampere architecture with 24GB GDDR6X memory and 10,496 CUDA cores for AI workloads, machine learning research, and model fine-tuning.
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RTX 2000 Ada
Compact professional GPU based on Ada Lovelace architecture with 16GB GDDR6 memory and 2,816 CUDA cores for AI workloads, machine learning, and professional applications in small form factor systems.
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.
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L40S
Universal data center GPU based on Ada Lovelace architecture with 48GB GDDR6 memory and 18,176 CUDA cores for AI inference, generative AI, and professional visualization workloads.
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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.
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H100 SXM
High-performance data center GPU based on Hopper architecture with 80GB HBM3 memory and 16,896 CUDA cores for large-scale AI training and high-performance computing workloads.
A100 PCIe
High-performance data center GPU based on Ampere architecture with 80GB HBM2e memory and 6,912 CUDA cores for AI training, machine learning, and high-performance computing workloads.
H100 NVL
Dual-GPU data center accelerator based on Hopper architecture with 188GB combined HBM3 memory (94GB per GPU) designed specifically for LLM inference and deployment.
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H100 PCIe
High-performance data center GPU based on Hopper architecture with 80GB HBM3 memory and 14,592 CUDA cores for AI training, machine learning, and enterprise workloads.
A40
Data center GPU based on Ampere architecture with 48GB GDDR6 memory and 10,752 CUDA cores for AI workloads, professional visualization, and virtual workstation applications.
A100 SXM
High-performance data center GPU based on Ampere architecture with 80GB HBM2e memory and 6,912 CUDA cores for large-scale AI training and high-performance computing workloads.
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LLM inference benchmarks.
Benchmarks were run using vLLM in May 2025 with Runpod GPUs
L40S
Universal data center GPU based on Ada Lovelace architecture with 48GB GDDR6 memory and 18,176 CUDA cores for AI inference, generative AI, and professional visualization workloads.
RTX A5000
Professional workstation GPU based on Ampere architecture with 24GB GDDR6 memory and 8,192 CUDA cores for balanced performance in AI workloads.
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.
H100 NVL
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.
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"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."
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https://media.getrunpod.io/latest/aneta-video-1.mp4
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"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."
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"Runpod has allowed us to focus entirely on growth and product development without us having to worry about the GPU infrastructure at all."
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https://media.getrunpod.io/latest/magic-studios-video.mp4
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"We could stop worrying about infrastructure and go back to building. That’s the real win.”
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“The main value proposition for us was the flexibility Runpod offered. We were able to scale up effortlessly to meet the demand at launch.”
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"After migration, we were able to cut down our server costs from thousands of dollars per day to only hundreds."
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Runpod’s scalable GPU infrastructure gave us the flexibility we needed to match customer traffic and model complexity—without overpaying for idle resources.
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