Small local models for repetitive work
3B
Use cheap capacity where the task is narrow
Routine classification, formatting, extraction and repetitive responses may not need the strongest cloud model. AIRE compares quality and throughput before routing those tasks locally.
Hybrid AI for a consulting organization
HY
Local throughput, cloud reasoning
Keep high-volume routine processing local or server-side while using stronger cloud models for difficult reasoning, external research or high-value decisions.
Existing GPU before a new purchase
GPU
Measure the bottleneck first
A workstation may still be sufficient after model quantization, task routing or lower-context workflows. New hardware is justified only after the real gap is known.
Provider-independent AI architecture
API
Keep your memory and workflows outside one provider
Separating data, state, prompts and workflow logic from the model provider makes ChatGPT, Qwen, local models or future providers replaceable.