Why is Meta's Llama called open-weight rather than open-source?
answer
- Downloadable does not mean OSI-approved
- Field-of-use limits break the definition
- Bespoke Meta agreement, not Apache-2.0
- Use restrictions plus a scale carve-out
- Weights are open; licence is conditional
basics
~20 sLlama weights are downloadable and usable commercially, but the Llama Community License imposes field-of-use limits through an acceptable-use policy and singles out very large operators for extra permission. Those restrictions fail the Open Source Definition, so the accurate term is open-weight.
solid answer
~50 sOpen source, as defined by the Open Source Initiative, requires among other things that a licence not discriminate against any person, group, or field of endeavour. Meta's Llama Community License does both: it incorporates an Acceptable Use Policy that forbids whole categories of application, and its additional commercial terms require operators above 700 million monthly active users to obtain Meta's permission. It is also a bespoke Meta agreement rather than a recognised licence like Apache-2.0 or MIT, and it carries naming, attribution and redistribution obligations. What you genuinely get is the weights: download, run offline, fine-tune, quantise, and redistribute under the same agreement, with no API dependency and no per-token fee. That is a real and valuable freedom — it just is not the legal category "open source", and saying so precisely is what an interviewer is listening for.
go deeper
Recall the phrase 'open weight, not open source' and one reason why: the licence restricts certain uses and singles out very large operators. Never describe Llama as MIT or Apache licensed.
Explain the two disqualifying clauses — the acceptable-use restrictions and the 700 million MAU carve-out — against the Open Source Definition's no-discrimination criteria, and note the licence is a bespoke per-release Meta agreement.
Turn it into a procurement answer: what open weights actually buy (in-boundary inference, no deprecation risk, GPU-cost economics, freedom to fine-tune) and what obligations survive (attribution, naming, redistribution terms, per-version review).
Own the vocabulary and the policy stance for the organisation — a closed / open-weight / open-source taxonomy applied consistently in architecture docs, and a rule that any model licence gets read per release rather than assumed from its category.
## Two different claims "Open source" is a legal-category claim about a licence. "Open weight" is a distribution claim about an artefact. Llama satisfies the second and not the first, and conflating them is the single most common error in this area. What Meta actually publishes is the trained parameters, a tokenizer, model cards and inference code, released under a bespoke *Llama Community License Agreement* that you accept before download. Anyone can take those weights, run them on their own hardware with no network call to Meta, inspect activations, fine-tune them, quantise them to run on a laptop, and redistribute the result — subject to the agreement's conditions. ## Why it fails the Open Source Definition The Open Source Definition maintained by the Open Source Initiative sets ten criteria a licence must meet. Llama's agreement breaches at least two of them. **No discrimination against persons or groups.** The additional commercial terms require any licensee whose products exceeded 700 million monthly active users in the calendar month before that version's release to request a licence from Meta, granted at Meta's sole discretion. A licence whose rights depend on who you are is not an open-source licence, however few entities are affected. **No discrimination against fields of endeavour.** The agreement incorporates Meta's Acceptable Use Policy by reference, which bars entire application categories. Open-source licences deliberately refuse to encode such use restrictions — that is why licences with "do no evil" or non-military clauses have never been OSI-approved either. Additionally, the agreement is unilaterally attached to a specific Meta-defined set of materials, imposes attribution and model-naming conditions, and is a different document for each release. None of that is fatal on its own — copyleft licences impose conditions too — but together with the two clauses above it puts Llama firmly outside the category. Separately, the OSI's Open Source AI Definition (published 2024) adds requirements around disclosure of training-data information; Llama does not publish its training corpus, which is another reason the label does not fit even under the AI-specific definition. ## What "open weight" buys you anyway The distinction is not academic pedantry that makes the licence worthless. Open weights give you capabilities a hosted API cannot: - **Data residency and air-gapping.** Inference runs entirely inside your boundary; no prompt leaves your network. This is often the whole reason a regulated organisation chooses Llama. - **No vendor deprecation.** A hosted model can be retired on the vendor's schedule; weights on your disk cannot. You control the upgrade timing. - **Cost structure.** You pay for GPUs and engineers, not per token — which wins at sustained high volume and loses at spiky low volume. - **Modification.** Fine-tuning, quantisation, pruning, and adapter stacking are all available and all permitted by the agreement. - **Auditability of behaviour.** You can reproduce a given output exactly, which matters for regulated review. What open weights do *not* give you is the ability to treat the licence as boilerplate. Because the terms are bespoke, someone has to read them per release. ## Saying it correctly in an interview A weak answer says "Llama is open source, so we can do whatever we like." A strong answer says: the weights are open and commercially usable, the licence is a bespoke Meta agreement rather than an OSI-approved one, the two disqualifying terms are the acceptable-use restrictions and the very-large-operator threshold, and the practical consequences for our team are attribution and naming obligations plus a per-version licence read. That answer demonstrates you would not embarrass the company in a compliance review — which is the actual thing being tested. ## The vocabulary that is now standard The industry has largely settled on a three-way vocabulary: *closed* (weights never leave the vendor, API access only), *open weight* (weights downloadable under a bespoke licence with conditions), and *open source* (weights and code under an OSI-approved licence with no field-of-use restrictions). Llama sits squarely in the middle bucket. Some other open-weight families do ship under standard permissive licences and therefore sit in the third bucket — which is exactly why using the terms precisely matters when comparing options in a design review.
- So what do we practically gain from open weights if it is not open source?Everything that depends on possessing the model rather than calling it: fully in-boundary inference for data residency or air-gapped deployment, immunity from vendor deprecation schedules, a GPU-cost rather than per-token-cost structure, and freedom to fine-tune, quantise, and modify. The licence conditions constrain *how you attribute and redistribute*, not whether you can run and adapt the model privately.
- Does calling it open source in our marketing copy create any real risk?Yes, two kinds. It is a factual misstatement that invites correction and reputational friction, since the OSI is explicit that field-of-use restrictions disqualify a licence. It also signals internally that no licence review is needed, which is how attribution and model-naming obligations get missed. The safe phrasing is 'open-weight model under the Meta Llama Community License', which is both accurate and short.
- Which specific clauses would you point to if asked to justify the distinction?Two. The acceptable-use restrictions incorporated by reference, which bar named categories of use and therefore discriminate against fields of endeavour. And the additional commercial terms, which require operators above 700 million monthly active users to obtain Meta's discretionary permission, discriminating against particular persons. The Open Source Definition forbids both, which is why no OSI approval exists for the agreement.
saying these in an interview costs you the question
- Calls Llama open source because the weights are downloadable
- Assumes Apache-2.0 or MIT terms apply to Llama weights
- Thinks open weights means no licence obligations at all
- Claims Meta publishes the training data alongside the weights
- Says the licence forbids commercial use entirely