Local AI vs Cloud AI.
Privacy, Cost, Speed, Control.
The right choice depends on your priorities. Local AI (Ollama, LM Studio) is private, free, and offline. Cloud AI (GPT-4o, Claude, Gemini) is more capable and requires no hardware. A complete comparison.
The honest summary
Cloud AI models are currently more capable than what you can run locally on consumer hardware. GPT-4o and Claude 3.5 Sonnet outperform Llama 3 8B on most complex tasks. This gap is closing, but it is real.
Local AI has genuine and important advantages: complete privacy, zero ongoing cost, offline capability, and no data retention by any third party. For tasks where a capable-but-not-frontier model is sufficient, and where privacy matters, local AI is the better choice. Skales supports both - use cloud models when you need maximum capability, switch to local when privacy or cost is the priority.
Detailed comparison
Six dimensions where local and cloud AI differ meaningfully.
Privacy and data handling
Local AI (Ollama)
Nothing leaves your machine. No server receives your text, documents, or audio. No data retention, no training on your inputs, no privacy policy to trust. Suitable for sensitive personal, legal, medical, and business data.
Cloud AI (GPT-4o, Claude, Gemini)
Text is sent to and processed by the provider's servers. Most providers have data handling commitments, but you are trusting their policies and infrastructure. Enterprise plans often offer stronger data protection terms.
Cost
Local AI (Ollama)
Free once set up. Ollama is free. Local models are free. The only cost is the electricity your hardware uses. No API limits, no usage caps, no subscription. Run a million tokens for pennies in electricity.
Cloud AI (GPT-4o, Claude, Gemini)
Priced per token. GPT-4o costs approximately $0.005 per 1K output tokens. For light use this is negligible (cents per session). For heavy use - bulk document processing, daily automation - costs compound. Enterprise pricing is higher.
Model capability
Local AI (Ollama)
Smaller models run on consumer hardware. Llama 3 8B and Mistral 7B are capable for most tasks but fall short of frontier models on complex reasoning, nuanced writing, and edge cases. Larger models (70B+) require high-end hardware.
Cloud AI (GPT-4o, Claude, Gemini)
GPT-4o, Claude 3.5 Sonnet, and Gemini 1.5 Pro represent the current capability frontier. They outperform local models on complex reasoning, code, creative tasks, and edge cases - sometimes significantly.
Offline availability
Local AI (Ollama)
Works with no internet connection. Useful on planes, in remote locations, in secure facilities, and anywhere connectivity is unreliable or restricted. The model runs entirely on your hardware.
Cloud AI (GPT-4o, Claude, Gemini)
Requires internet connectivity. Service outages, rate limits, and network issues can interrupt availability. Not suitable for offline use cases or locations with restricted internet access.
Hardware requirements
Local AI (Ollama)
Small models (7B) run on 8GB RAM. Larger models need more RAM and benefit from a GPU. High-end local model inference requires 24GB+ VRAM for top-tier models. Consumer hardware has real limits on what is practical.
Cloud AI (GPT-4o, Claude, Gemini)
Requires only an internet connection and a device capable of running the client application. No GPU, no RAM constraints, no storage beyond the client app. Anyone can access frontier model capability on a basic laptop.
Speed
Local AI (Ollama)
Speed depends on your hardware. A modern CPU processes small models at reasonable speeds. A good GPU is significantly faster. Inference speed on consumer hardware is typically lower than cloud APIs.
Cloud AI (GPT-4o, Claude, Gemini)
Cloud providers run highly optimised inference infrastructure. Responses from frontier models are typically fast - often faster than running a smaller model locally on a mid-range laptop CPU.
Choose based on your situation
Use local AI when:
- ✓ Privacy is non-negotiable
- ✓ You need offline capability
- ✓ High volume usage would make cloud costs significant
- ✓ Tasks are within the capability of smaller models
- ✓ You have suitable hardware (8GB+ RAM)
Use cloud AI when:
- ✓ Maximum reasoning capability is required
- ✓ You are using a low-spec machine
- ✓ Usage volume is light (costs remain low)
- ✓ Speed is more important than privacy
- ✓ The content is not sensitive
Quick comparison
| Feature | Local AI (Skales + Ollama) | Cloud AI |
|---|---|---|
| Privacy | Complete - no data leaves device | Data sent to provider |
| Cost | Free (after hardware) | Per-token or subscription |
| Internet required | No | Yes |
| Model quality | Good (Llama, Mistral) | Best (GPT-4, Claude) |
| Speed | Depends on hardware | Generally fast |
| GDPR compliance | Inherent | Requires DPA |
Skales supports both - switch based on the task
Free for personal use. Switch between local and cloud models at any time.
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