Learn · Foundations · What is Local Inference?
Cloud vs Local
In plain English
Cloud AI is like asking a genius across the world for help via mail. 🌍 Local AI is like having that genius sit next to you in the room. 🧑🏫
What is actually going on
Cloud inference relies on centralized massive compute clusters (e.g., thousands of H100s) accessed via REST APIs. Local inference utilizes the user's heterogeneous hardware, bounded by local RAM and thermal limits.
Why it matters
Choosing between cloud and local dictates your application's privacy guarantees, recurring costs, and uptime reliability.
Another way to think about it
Cloud is a taxi (pay per ride); Local is owning a car (upfront cost, free rides). 🚕 vs 🚗
Check yourself
Which approach typically offers absolute data privacy?
- Cloud APIs
- Local Inference
- Hybrid Cloud
- Public Endpoints
Show answer
Local Inference — Since data never leaves your device, local inference guarantees privacy.
What is the primary ongoing cost for cloud inference?
- Electricity bill
- Hardware maintenance
- API usage fees per token
- Cooling costs
Show answer
API usage fees per token — Cloud providers usually charge based on the number of tokens processed.
Cloud models are always smaller than local models.
- True
- False
Show answer
False — Cloud models (like GPT-4) are typically massive since they run on giant datacenters, whereas local models are smaller to fit on consumer hardware.