Moreover.ai · Open Source AI Infrastructure Framework

AI Infrastructure
Workload Sizing

Interactive AI infrastructure framework to evaluate how modern LLM workloads scale across GPU compute, VRAM capacity, context windows and inference concurrency. Powered by realistic benchmark rankings and infrastructure-aware sizing.

No hallucinated sizing Official metadata first Transparent VRAM estimates Open-source methodology
Total Models
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Providers
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Families
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Open Weight
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With Benchmarks
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GPUs
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AI Infrastructure & Inference Workload Sizing

Define the workload and infrastructure constraints. The dashboard filters compatible models and exposes memory pressure through the heatmap.

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Comfortable = estimated VRAM ≤ 80% of GPU VRAM. Limited = estimated VRAM ≤ 95% of GPU VRAM. Concurrent users multiply KV cache, not model weights.

Infrastructure Capacity Heatmap

Memory pressure across context size and concurrent users for the selected model and GPU.

Model Name Provider Family Parameters Context Availability Infrastructure Fit
Click a model for architecture, benchmark and memory details. Select a compatible model in the workload panel to display the heatmap, or use Map from the table.