Great comparison! The local vs cloud debate is one of the most common questions we see.
Our take: it depends on what you're doing.
Local models are great for:
- Privacy-sensitive work
- Offline development
- Quick tests and prototyping
- Simple tasks that don't need frontier intelligence
Cloud models are better for:
- Production work that needs reliability
- Hard reasoning and complex coding
- Access to the latest frontier models
- Teams that don't want to manage GPU infrastructure
For most developers, the sweet spot is a mix. Use local models for routine work, and cloud API for hard tasks.
We use JZS Token as our cloud API gateway. One OpenAI-compatible endpoint, 40+ models. Switching between models is just changing the model name. We keep local models for offline work, and use the gateway for everything else.
The cost savings from mixing and matching are significant. You don't have to pay for the most expensive model for every single task.
Nice breakdown. This should help a lot of developers decide what's right for them.
Great comparison! The local vs cloud debate is one of the most common questions we see.
Our take: it depends on what you're doing.
Local models are great for:
Cloud models are better for:
For most developers, the sweet spot is a mix. Use local models for routine work, and cloud API for hard tasks.
We use JZS Token as our cloud API gateway. One OpenAI-compatible endpoint, 40+ models. Switching between models is just changing the model name. We keep local models for offline work, and use the gateway for everything else.
The cost savings from mixing and matching are significant. You don't have to pay for the most expensive model for every single task.
Nice breakdown. This should help a lot of developers decide what's right for them.