Which GPU fits which workload? 10 workloads × 12 GPU models, benchmarked.
10 common workloads benchmarked against 12 GPU models. Search or filter by category, click any cell for detailed reasoning.
Workload | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AI/ML Training | ||||||||||||
| LLM Inference | ||||||||||||
| RAG/Vector Search | ||||||||||||
| Computer Vision | ||||||||||||
| 3D Rendering & VFX | ||||||||||||
| Video Transcoding | ||||||||||||
| HPC/Scientific | ||||||||||||
| Virtual Workstation/VDI | ||||||||||||
| CAD/Engineering | ||||||||||||
| Simulation & Digital Twins |
Click any cell in the matrix to see detailed reasoning for that GPU + workload combination.
Estimates. Ratings reflect typical fit for production workloads. Actual performance depends on model size, batch shape, software stack, and cooling. Always validate with your own benchmarks before procurement.
Choosing the right GPU for your workload is harder than it looks. A GPU that's perfect for LLM training might be overkill (and expensive) for RAG embeddings. A GPU that's great for CAD workstations has no place in an HPC cluster. Most teams pick based on what they've heard of — H100 for everything — and overspend.
The GPU Workload Matrix benchmarks 10 common workloads against 12 GPU models, from H100 and B200 down to T4 and L4. Each cell shows a 4-tier rating (Best / Better / Good / Not recommended) with detailed reasoning — not just a checkbox, but the actual trade-offs.
Filter by workload category (AI & ML, Rendering & Media, HPC, Workstation) to find the right GPU for your use case. Click any cell for detailed reasoning.
Compare H100, A100, L40S, and consumer GPU pricing across 8+ providers — benchmarked against your actual workload, not affiliate payouts.
Adapt open-source LLMs (Llama, Mistral, Qwen, DeepSeek) to your domain — with LoRA, QLoRA, instruction tuning, and safe deployment guardrails.
End-to-end ML pipelines — experiment tracking, model registry, feature stores, CI/CD for models, drift detection, and rollback. Built on Kubernetes.
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