AI Platform
Exogram vs Meta Llama (Open Source)
“Open weights don't include open guardrails.”
What Meta Llama (Open Source) Does
- •Meta releases open-weight models (Llama 3, Llama 4) that anyone can deploy.
- •No built-in tool governance. No execution control. No safety infrastructure for function calls.
- •Self-hosted deployments run with whatever guardrails the developer adds — which is usually none.
- •The model is the product. Everything else is your responsibility.
What Exogram Does
- ▸Exogram provides the governance layer that open-source models completely lack.
- ▸Self-hosted Llama deployments have zero native execution boundaries. Exogram is the deterministic gate.
- ▸Same 0.07ms enforcement, same 8 policy rules, same zero false negatives — regardless of model size or deployment method.
- ▸Exogram is the fastest way to add production-grade governance to any open-source model deployment.
Key Differences
| Dimension | Meta Llama | Exogram |
|---|---|---|
| Governance | None (your responsibility) | Full deterministic enforcement |
| Tool Call Safety | None built-in | 8 policy rules per request |
| Self-Hosted Support | Yes (that's the product) | Yes (works with any deployment) |
The Verdict
Deploy Llama for cost-effective intelligence. Deploy Exogram because open-source models have zero built-in execution governance.
Is Meta Llama (Open Source) vulnerable to execution drift?
Run a static analysis on your LLM pipeline below.
STATIC ANALYSIS
Frequently Asked Questions
Does Exogram work with self-hosted Llama?
Yes. Exogram is model-agnostic. It works with vLLM, Ollama, TGI, and any Llama deployment that produces tool calls.
Why do open-source models need Exogram more than commercial models?
Commercial models have some content safety filters. Open-source models have none. Neither has execution governance — but open-source models lack even basic safety infrastructure. Exogram fills both gaps.