FAQ Hub
This FAQ is intentionally practical. It covers runtime behavior, upload-free workflows, hardware expectations, and what to do when browser AI behaves like browser AI instead of a perfectly provisioned server environment.
Yes. Browser transcription is possible through WebAssembly, ONNX Runtime Web, and related execution layers. The exact speed and stability depend on model choice, quantization, and whether the browser can use GPU acceleration.
WebGPU gives the browser a more capable path to run model workloads on compatible graphics hardware. In practice that can improve throughput and reduce waiting time for medium or large inference jobs.
Yes. Cowslator is built around local browser processing, so transcription can happen on-device without mandatory server upload as the default workflow.
Common causes include model size exceeding available memory, unstable GPU paths, long media files stressing the runtime, or browser tabs competing for resources. Adaptive fallback is important precisely because these conditions are normal in the wild.
There is no single number. Smaller quantized models may fit comfortably on mainstream laptops, while larger models can consume multiple gigabytes and become unrealistic for browser execution on lower-end hardware.
Yes. Batch workflows are designed for queue-based processing so users can feed folders of audio or video files into one transcription session.
The intended workflow is local browser execution. That means the user’s machine performs the inference rather than sending every file to a remote transcription service first.
WebGPU can be much faster on supported devices, while WASM is usually the broader compatibility path. Reliable products use both because not every machine can sustain GPU acceleration well.
Because finishing reliably is often better than attempting a larger model that overwhelms the device. Adaptive inference trades theoretical maximum quality for real completion on mixed hardware when necessary.
Yes. Local transcription is often the first step toward SRT, LRC, and editing-friendly text exports used by creators, podcasters, and documentary teams.
Modern Chromium-based browsers generally expose the strongest WebGPU support today, but compatibility changes over time and fallback behavior still matters for a robust experience.
No. Cloud systems remain useful for centralized automation, shared dashboards, and organization-wide orchestration. Local-first tools simply offer a different set of tradeoffs that many users prefer for privacy and control.
Why local processing matters beyond privacy language.
How hardware-aware scheduling prevents avoidable failures.
Practical notes for freezes, slowdowns, and backend fallback.
Tradeoffs between acceleration and broad compatibility.
