Comparison
Cloud vs On-Device Dictation
Cloud and on-device dictation can both work well, but they optimize for different constraints. The right choice depends on your latency tolerance, privacy requirements, and workflow consistency needs.
Tradeoff matrix
- Latency: on-device usually wins on post-speech responsiveness.
- Privacy boundary: on-device reduces voice transfer risk.
- Reliability: on-device remains available in offline or constrained networks.
- Model flexibility: cloud options may offer broader model choices.
When cloud-first is acceptable
If connectivity is stable and privacy constraints are light, cloud dictation can be workable for low-frequency usage.
When on-device is the better fit
High-frequency writing, strict confidentiality, and performance-sensitive workflows benefit most from local deterministic processing.
Benchmark qualifier
Based on Almond internal testing (February 15, 2026): same 20-second spoken phrase, measured from end of dictation to visible final text result versus Wispr Flow and other cloud-first dictation models.
- Test date: 2026-02-15
- Input: Same 20-second spoken phrase
- Metric: Elapsed time from end of dictation to visible final result
- Comparison group: Wispr Flow and other cloud-first dictation models
Related resources
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