What just changed?
Meta’s Llama models were approved for use by U.S. government agencies through the GSA, and Meta announced availability for U.S. allies in Europe and Asia—a strong signal that open-weight deployments with enterprise controls are now procurement-friendly. For buyers, that expands the menu beyond fully closed models and helps with cost, portability, and vendor flexibility.
Why enterprises should care
Open-weight options let you control data pipelines, apply custom retrieval and evals, and—if required—self-host components while still consuming managed offerings from major clouds. On Google Cloud, for example, Llama 3.1 is available as a fully-managed model on Vertex AI, giving teams governance, quotas, and monitoring out of the box without standing up infra from scratch.
How to evaluate (service playbook)
Start with a narrow, traceable use case—knowledge assistant for support or internal research. Wire RAG with freshness + permissions, add guardrails and logging, and run a head-to-head against your incumbent closed model. Compare answer quality, latency, cost per resolved query, and maintainability. If you need extra control, explore self-deployed Llama on managed infrastructure for fine-tunes and custom adapters while keeping data in your environment.
Governance & procurement
Government-grade acceptance doesn’t remove your responsibilities: keep PII handling, redaction, retention, and evals in your CI/CD; ensure contract terms allow export of prompts/logs; and insist on clear SLAs and security attestations from any managed provider. If your organization operates in regulated industries, map this to your sector controls before scaling.