An honest look at what separates on-device AI from cloud-based alternatives. Kynora wins on privacy and offline availability. Cloud AI wins on raw model size. Here is exactly what that means for your work.
Works fully offline with zero cloud data transmission — by architecture, not policy
Native macOS, iPadOS, and iOS app with on-device AI inference and a persistent local knowledge base
Page-level citations tracing every answer to its exact source in your documents — fully on-device
Larger server-side models for general knowledge and open-ended reasoning at scale
The Cloud AI column reflects typical characteristics of consumer cloud AI products. Individual products vary significantly — some enterprise offerings may differ from the general patterns shown here. Kynora column reflects planned launch functionality. Verify capabilities of any specific product with its provider before making purchase or compliance decisions.
| Feature | ✦ Kynora | Cloud AI (Typical) |
|---|---|---|
| Works fully offline | ✓ | ✗ |
| Data stays on your device | ✓ | ✗ |
| No cloud account required | ✓ | ✗ |
| Air-gap compatible | ✓ | ✗ |
| Document upload & chat (On-device AI) | ✓ | ✗ |
| Page-level citations (On-device AI) | ✓ | ✗ |
| Persistent knowledge base (On-device AI) | ✓ | ✗ |
| OCR for scanned documents (On-device AI) | ✓ | ✗ |
| Native macOS app (On-device AI) | ✓ | ✗ |
| Native iPadOS + iOS app (On-device AI) | ✓ | ✗ |
| Open model support | ✓ | ✗ |
| No training on your data | ✓ | ✓ |
| Ongoing subscription cost | TBD | $10–$200+ /month |
| General knowledge (world facts) | Via local model (Till Model Trained date) | ✓ |
| Real-time web search | ✗ | ✓ |
Last updated 2026-07-28. Cloud AI column reflects typical characteristics of consumer cloud AI products; individual products and enterprise tiers vary. Kynora column reflects planned launch functionality. Join the waitlist for updates.
Cloud based AI document tools are architected to transmit your content to external servers for processing — this is a fundamental architectural characteristic, not a configuration option. For professionals with confidentiality obligations — this architecture raises questions about using cloud AI for sensitive document work that each professional must assess with their own ethics and compliance counsel.
Kynora also wins on offline availability (works anywhere, always), native experience across macOS, iPadOS, and iOS, and the absence of ongoing subscription costs.
The largest cloud AI models are trained on far more data and have significantly more parameters than any model that can run locally today. For open-ended reasoning, creative tasks, or questions requiring broad world knowledge, large server-side models outperform local models in most benchmarks.
Real-time web search is also not available in an offline-first tool by design. If you need live information from the internet, cloud AI is the right tool for that specific use case.
Most people choose AI tools based on output quality in demos. The real differentiator for professional use is whether the tool can be trusted with the documents you actually have — not the documents you would be comfortable uploading to a cloud provider.
For your most sensitive work, the relevant question is not "which model is smarter?" It is "which model is permitted to see this?" On-device AI answers that question permanently.
The quality gap between local and cloud models is narrowing rapidly. The latest open-weight models now match or exceed earlier cloud generations for document-specific tasks. For RAG workloads — where the model is given precise retrieved context rather than relying on general knowledge — a well-configured local model often performs comparably to much larger cloud models on your specific documents.
Join the waitlist and be first to know when Kynora launches on Mac, iPad, and iPhone.