model · Meta
Llama development
Open-weight models you can host yourself, the default when data cannot leave your building.
- Category
- model
- Vendor
- Meta
- We use it for
- 4 capabilities
The honest assessment
- What it is
- Open-weight models you can host yourself, the default when data cannot leave your building.
- Strongest at
- full control, no per-token cost, and viable air-gapped deployment
- Trade-off
- you own the infrastructure, the scaling and the evaluation work that a hosted API absorbs for you
- Category
- model
- Vendor
- Meta
We hold no reseller commission on Meta. That is what makes the trade-off line above worth reading. It costs us nothing to tell you when this is the wrong choice.
Building with Llama
Llama is strongest at full control, no per-token cost, and viable air-gapped deployment. We reach for it when that is the property a workload actually depends on, and we say so when it is not.
Self-hosting Llama is a commitment rather than a configuration. You take on GPU capacity planning, serving infrastructure, scaling under load and the evaluation work a hosted provider absorbs quietly. That is worth it when data residency is absolute or volume is sustained and high, and rarely worth it below either threshold.
The licence is worth reading before you build on it. Open weights is not the same as open source, and the terms carry usage restrictions that occasionally matter for commercial products.
Integration comes before intelligence. A model that cannot reach your systems of record is a demo with good manners. Six weeks to something running in production, not six quarters to a strategy document.
Alternatives in model
Questions
What is Llama best at?
Full control, no per-token cost, and viable air-gapped deployment.
When would you not use Llama?
You own the infrastructure, the scaling and the evaluation work that a hosted API absorbs for you. We would look at Claude or OpenAI GPT in that situation.
Do you have a commercial relationship with Meta?
No. We hold no reseller commission on any technology we recommend, which is what lets the trade-off above be stated plainly.
Can you work with our existing Llama setup?
Yes. We would rather extend and stabilise something that already works than introduce a parallel system your team has to learn.
Working with Llama?
Tell us the workload and we will tell you whether this is the right tool for it.
Or email bd@dtrasglobal.com · call +91 74118 77878