CPU-based transcription

Cloud transcription services have made audio processing convenient, but they have made it costly and data-risky. Every minute of audio uploaded to the cloud triggers a meter. A one-hour meeting costs $1–5 depending on the service. Multiply that across a team, a department, or a year, and the bill becomes significant. And because the audio is uploaded, you are trusting the vendor with sensitive conversations: medical details, business strategy, legal advice, customer data.

GPU-accelerated transcription is even more restrictive. It requires specialized hardware (an NVIDIA card) and additional API keys or licenses. For most organisations, that is not feasible. Laptops in the field, budget machines, and older equipment do not have GPUs. If your team can only transcribe on machines with graphics cards, you have built a bottleneck into your workflow.

CPU-based transcription removes both constraints. Modern processors — even mid-tier or older ones — are more than capable of running transcription models locally. The speed trades off against GPU acceleration, but for an office worker who records a meeting and processes it overnight, or a lawyer who transcribes a deposition during quiet hours, CPU speed is not the constraint. Ownership and privacy are.

Running on CPU means you can transcribe on any Windows laptop, without additional hardware, without API keys, and without cloud costs. The machine you already own does the work. The audio never leaves your device. You do not pay per minute. And because the models are bundled inside the installer, there is nothing to configure or maintain.