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Assess · Meta Llama 4

Can you own it?

Ownership levelPartialnone·limited·partial·substantial·fullAnalytical input C ยท 70.8/100

This page is a projection of the one entry record, the Use & modify and Transparency factors that Assess covers. The full verdict is set by all four factors together, floor-weighted so the weakest caps the whole.

Which domain expands which factor
  • AssessUse & modify + Transparency
  • ImplementData control + Reliability
  • UseReliability
  • SupportTransparency

Intended & out-of-scope use

Meta Llama 4 is the natively multimodal, mixture-of-experts generation: Scout and Maverick (released) and the larger Behemoth. For non-EU users it is a strong, well-supported multimodal family for general, coding, multimodal, and long-context work. It is a separate entry from the Llama 3.x text line (the meta-llama entry) because of a licence divergence that actually bites.

Out-of-scope, decisively for EU-domiciled entities: the Llama 4 multimodal licence is not granted to individuals domiciled in, or companies with a principal place of business in, the EU - so an EU-domiciled organisation cannot licence these models at all (only downstream end users of someone else's product are exempted).

Known limitations, bias & failure modes

The dominant limitation is legal, not behavioural: the EU-domiciled multimodal licence gap, the systemic-risk status of the large models, the 700M-MAU commercial trigger, the "Built with Llama" naming duty, and the download access gate. Training data and code are closed, and Maverick/Behemoth need very large infrastructure.

Openness tier & components

gated_open tier (dimension score 3 on access). Weights are downloadable after click-through acceptance and documentation is strong, but training data and code are closed and the licence is conditional. The licence conditions are scored under legal, not openness.

License terms & what you may do

The Llama 4 Community Licence (non-OSI). The load-bearing clause is in the incorporated AUP, verbatim: "with respect to any multimodal models included in Llama 4, the rights granted under Section 1(a) ... are not being granted to you if you are an individual domiciled in, or a company with a principal place of business in, the European Union" (downstream end users exempted). Because Llama 4 is multimodal, EU-domiciled entities get no licence. The licence also keeps the 700M-MAU commercial trigger, "Built with Llama" naming/attribution, an AUP with six prohibited-use categories, and California governing law. The Llama 3.1 text models do not carry the EU carve-out. This is why legal scores 2 and EU-domiciled ownership is effectively none.

Supply-chain provenance

The canonical source is the verified, access-gated meta-llama organisation on Hugging Face, distributing safetensors with checksums and per-version licence tags, with no malicious-checkpoint incident. Major clouds (Bedrock, Vertex, Together, Groq) host Llama 4 - a hosted end-user product is the AUP-exempted path for EU end users, but not for EU-domiciled entities building on the weights. Pin the revision and verify checksums.

EU AI Act posture

GPAI, and systemic-risk for the large models (>1e25 FLOP). The Article 53 open-source exemption does not apply for two independent reasons: the Community Licence is not FOSS, and the large models are systemic-risk. Meta also declined the EU GPAI Code of Practice and publishes no copyright policy or training-content summary. And the EU-multimodal carve-out denies EU-domiciled entities a licence outright. For EU-domiciled use, prefer the Llama 3.1 text models (the meta-llama entry) or a non-Llama family. Legal scores 2, with a hard flag.

Benchmarks & evaluation

Llama 4 Maverick is competitive among open multimodal models, and the family adds native multimodality and very long context. OneHill has not re-run these benchmarks, so performance is capped at 4 and no specific figures are asserted as verified.

Independent safety evaluation

A genuine strength: Meta ships Llama Guard (input/output moderation) and Prompt Guard (prompt-injection/jailbreak detection) with the family, alongside documented safety tuning. No broad independent multimodal red-team is aggregated here, so safety is a strong 4 rather than 5.

How this scores

The ownership factors this domain covers, drawn from the one entry record.

1

Use and modify freelyCan you run, modify and adapt it with no gate and no field-of-use trap?

Moderate

For non-EU users the Community Licence permits commercial use and modification below 700M MAU, with an AUP and 'Built with Llama' naming - moderate. But for EU-domiciled individuals/companies the multimodal licence is NOT granted at all, so their use-and-modify is effectively none. Scored moderate as the global position, with the EU carve-out flagged as decisive for EU entities.

How this scores (AOI sub-dimensions)
Openness3/5how much is released - weights, data, code, licence - and how freelyGated-open tier: weights are downloadable (after click-through acceptance) with strong documentation, but training data and code are closed and the licence is conditional.
Legal2/5how permissive and clean the licence is for real commercial useThe weakest legal position in the Llama family: the Community Licence is non-OSI with a 700M-MAU trigger and AUP, AND - unlike the Llama 3.x text models - denies EU-domiciled entities any licence to the multimodal models, AND the large models are systemic-risk (voiding the open-source exemption).
2

TransparencyDo you know what it is: weights, training, behaviour, and legible terms?

Moderate

Weights are inspectable and documentation is strong, but training data and code are closed - open weights, closed process, so moderate.

How this scores (AOI sub-dimensions)
Provenance4/5how well we can trace and verify what went into the modelCanonical, verified (and access-gated) meta-llama org on Hugging Face distributing safetensors with checksums and per-version licence tags; no malicious-checkpoint incident on the canonical org.
Governance3/5how accountable and well-documented the publisher isA named, accountable US provider (Meta) with a verified org and a reporting path (LlamaUseReport@meta.com), meeting the score-3 anchor.
What this means for adoptionFor non-EU users you partially own self-hosted Llama 4: it runs on your infrastructure, performs strongly as a multimodal family, and pairs with Meta's Llama Guard and Prompt Guard (reliability strong), but the Community Licence's 700M-MAU trigger, naming conditions, and access gate keep use-and-modify at moderate - ownership partial. For EU-domiciled individuals and companies the picture is worse: the licence denies you any grant to the multimodal models, so your effective ownership is none - prefer the Llama 3.1 text line (the meta-llama entry, no EU clause) or a non-Llama family. Either way, check the 700M-MAU trigger, honour the Llama attribution terms, and confirm your domicile against the AUP before use.

Sources

The same evidence records as the entry sheet. Read means the text was verified; unverified means it is known to exist but not yet read.

Licenceread2026-08-03
Llama 4 Community License, read verbatim (via Meta's canonical GitHub mirror meta-llama/llama-models): the "Additional Commercial Terms" 700M-MAU threshold ("greater than 700 million monthly active users in the preceding calendar month, you must request a license from Meta"), the "Built with Llama" attribution clause, California governing law, and the incorporated AUP carrying the EU multimodal restriction.
Terms of serviceread2026-08-03
Llama 4 Acceptable Use Policy, read verbatim: "With respect to any multimodal models included in Llama 4, the rights granted under Section 1(a) ...
Model cardread2026-08-03
Llama 4 on the verified, access-gated meta-llama HF org: Scout (109B/17B, very long context), Maverick (400B/17B), Behemoth (larger); natively multimodal MoE; safetensors with checksums and a llama4 licence tag; hosted on Bedrock/Vertex/Together/Groq.
Third-party analysisunverified2026-08-03
On public leaderboards Llama 4 Maverick is competitive among open multimodal models; the family adds native multimodality and very long context.
Model cardunverified2026-08-03
Meta ships Llama Guard (input/output moderation) and Prompt Guard (prompt-injection/jailbreak detection) with the Llama family and documents safety tuning; no broad independent multimodal red-team is aggregated here.