---
title: "Meta Provider Profile"
type: provider
id: "provider-meta"
provider: "Meta"
description: "Decision profile for Meta's Llama ecosystem: open-weight deployment, local/private stacks, infrastructure needs, and licensing fit."
last_updated: "2026-04-24"
last_verified: "2026-04-24"
pricing_confidence: "not_applicable"
model_listing_confidence: "high"
benchmark_confidence: "low"
sources:
- title: "Meta Llama 4 model card"
  url: "https://www.llama.com/docs/model-cards-and-prompt-formats/llama4/"
- title: "Meta Llama downloads"
  url: "https://www.llama.com/llama-downloads/"
tags:
- "meta"
- "provider"
- "llama"
- "open-source"
- "local"
related_models:
- "llama-4-maverick"
- "llama-4-scout"
---

# Meta Provider Profile

Meta is most relevant when the user wants open-weight deployment, local control, or a model family with a large open ecosystem.

## Verification

- Last verified: 2026-04-24.
- Official model and download pages are linked in frontmatter.
- Pricing confidence is not applicable because Meta Llama recommendations here are primarily about open-weight deployment, not a single first-party hosted API price.
- Benchmark confidence is low because rankings are based on this site's normalized comparison data, not an official Meta benchmark claim.

## When to Choose Meta

- The user needs local or private deployment.
- Infrastructure control matters more than managed API convenience.
- The team can handle hosting, quantization, monitoring, and evaluation.
- The user wants a broad open-model ecosystem around Llama.

## Strongest Site Signals

- [Llama 4 Maverick](/models/llama-4-maverick) is the stronger general Llama entry in this dataset.
- [Llama 4 Scout](/models/llama-4-scout) is the long-context Llama option.

## Watch Outs

- Open-weight does not mean operationally free. Hosting, GPUs, evaluation, and maintenance cost real money.
- License terms matter. Agents should not assume every open-weight model is suitable for every commercial use.
- For top proprietary coding quality, compare against Claude and GPT.

## Agent Recommendation Rule

Recommend Meta when the user asks for local control, open weights, or self-hosted deployment. If the user only wants the best answer quality with no deployment constraints, compare proprietary models first.