Local AI Inference
A method of running large AI models for inference on local hardware, such as consumer-grade GPUs, without relying on cloud-based APIs. Data remains on-premises throughout the process. Performance is constrained by available hardware, and the total cost of ownership includes factors such as electricity consumption and hardware depreciation.
Core Facts
Timeline (last 90 days)
The cost of running large models locally is measured in time (electricity cost per hour), while the cost of cloud API is measured in throughput (per million tokens), and the two must be converted to the same basis for a fair comparison.
Estimated at 70 tokens/second, approximately 252 million tokens can be generated in one hour, translating to an electricity cost of approximately €0.48 per million tokens.
For high-frequency, long-duration, continuously saturated workloads, the marginal electricity cost advantage of local inference becomes apparent.
The essential difference between local AI inference and cloud inference lies in where the computation occurs: cloud inference requires sending prompts and context data to a remote server for computation by the provider's GPUs, while local inference downloads the model weights to the user's device and performs the forward pass on-device.
The core appeal of local AI lies in privacy, low latency, and offline availability.
All Facts (5)
The core appeal of local AI lies in privacy, low latency, and offline availability.
70%UnverifiedThe cost of running large models locally is measured in time (electricity cost per hour), while the cost of cloud API is measured in throughput (per million tokens), and the two must be converted to the same basis for a fair comparison.
50%UnverifiedEstimated at 70 tokens/second, approximately 252 million tokens can be generated in one hour, translating to an electricity cost of approximately €0.48 per million tokens.
50%UnverifiedFor high-frequency, long-duration, continuously saturated workloads, the marginal electricity cost advantage of local inference becomes apparent.
50%UnverifiedThe essential difference between local AI inference and cloud inference lies in where the computation occurs: cloud inference requires sending prompts and context data to a remote server for computation by the provider's GPUs, while local inference downloads the model weights to the user's device and performs the forward pass on-device.
50%