Meta Llama

What Meta Llama is

Meta Llama is Meta's family of open-source large language models that you can download, fine-tune, distill, and deploy anywhere, rather than a hosted API you call directly.

It is open model weights, not a first-party API, so its fit in the LLM-API category is loose; you typically access Llama through a provider or your own stack. The appeal is ownership: the model is yours to run, and there is no per-call fee to a vendor.

The stance is open-source AI you can deploy anywhere, and the value is control over where the model runs and what it costs at scale.

What you can do with it

You obtain the model weights under a permissive license, run them on your own hardware or a partner cloud, and build applications without per-call fees, so the loop is download, adapt, deploy, aimed at teams wanting ownership and on-prem control.

Because you self-host, you choose the hardware, the region, and the update cadence, which is the opposite of a managed API where those are decided for you. Fine-tuning and distillation let you shrink or specialise the model for your use.

For teams that cannot send data to a third party, running the weights locally is the feature, not a workaround.

Who it is for

It suits developers and enterprises wanting control of the model and its environment.

It suits teams that need on-prem or private deployment for residency or cost reasons.

What to keep in mind

Pricing is free to download and self-host with no usage fee, which is a genuine plus, and because it is free, confirm the license scope before you ship something commercial. Free weights still carry terms, and those terms decide what you may sell.

The compliance stance is license-based: review the community or acceptable-use license for commercial thresholds, and as you self-host you own security and data residency, so scope where the model runs. The license, not a certification page, is the compliance document here.

A practical point: open weights move the work to you. You provision the GPUs, you patch, you keep the model current, and you carry the responsibility for what it outputs. The freedom from a vendor is real, and so is the operational load it replaces. If you have no one to run GPUs, the free weights are still a cost, just paid in engineering time instead of a bill, and that trade is the one to be honest about.

Two practical points

Confirm the license and your hosting, and mind the commercial thresholds, because free to download is not the same as free to sell, and self-hosting means you own security and residency.