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Llama model family history

Snapshots are retained. Added and removed counts compare normalized words with the preceding revision.

r5Seed corpus update
+4 / −2 words

As of 2026-11-04

Llama is a Meta downloadable model family distributed under release-specific community licenses. Open weights describe access to parameters; they do not by themselves establish an OSI-approved open-source license.

Revision snapshot

Overview. Llama is a Meta downloadable model family distributed under release-specific community licenses. Open weights describe access to parameters; they do not by themselves establish an OSI-approved open-source license.

Mechanism and context. Llama denotes a sequence of downloadable model releases rather than one stable checkpoint. A release combines parameter artifacts, architecture and usage documentation, and version-specific community terms, so technical access and granted reuse rights must be recorded separately.

Practical use. For a local or hosted deployment, pin the exact checkpoint and revision, read its accompanying terms, record the inference format and quantization, and evaluate the resulting system on the intended workload. A family-level comparison cannot capture those choices.

Related reading. Read Open source, open weight, and open access for precise terminology, Hugging Face Hub for artifact-level records, Model quantization for lower-precision deployment, and Model evaluation for workload evidence.

r4Seed corpus update
+0 / −40 words

As of 2026-07-13

Llama is Meta's downloadable model family distributed under release-specific community licenses. Open weights describe access to parameters; they do not by themselves establish an OSI-approved open-source license.

Revision snapshot

Overview. Llama is Meta's downloadable model family distributed under release-specific community licenses. Open weights describe access to parameters; they do not by themselves establish an OSI-approved open-source license.

Mechanism and context. Llama denotes a sequence of downloadable model releases rather than one stable checkpoint. A release combines parameter artifacts, architecture and usage documentation, and version-specific community terms, so technical access and granted reuse rights must be recorded separately.

Practical use. For a local or hosted deployment, pin the exact checkpoint and revision, read its accompanying terms, record the inference format and quantization, and evaluate the resulting system on the intended workload. A family-level comparison cannot capture those choices.

Related reading. Read Open source, open weight, and open access for precise terminology, Hugging Face Hub for artifact-level records, Model quantization for lower-precision deployment, and Model evaluation for workload evidence.

r3Seed corpus update
+128 / −81 words

As of 2026-07-13

Llama is Meta's downloadable model family distributed under release-specific community licenses. Open weights describe access to parameters; they do not by themselves establish an OSI-approved open-source license.

Revision snapshot

Overview. Llama is Meta's downloadable model family distributed under release-specific community licenses. Open weights describe access to parameters; they do not by themselves establish an OSI-approved open-source license.

Mechanism and context. Llama denotes a sequence of downloadable model releases rather than one stable checkpoint. A release combines parameter artifacts, architecture and usage documentation, and version-specific community terms, so technical access and granted reuse rights must be recorded separately.

Practical use. For a local or hosted deployment, pin the exact checkpoint and revision, read its accompanying terms, record the inference format and quantization, and evaluate the resulting system on the intended workload. A family-level comparison cannot capture those choices.

Limitations and evidence. Downloadable parameters support inspection and alternative deployment, but that fact alone does not establish an OSI-approved open-source license or equal behavior across derived checkpoints. Repository metadata and third-party packaging should be checked against the original release record.

Related reading. Read Open source, open weight, and open access for precise terminology, Hugging Face Hub for artifact-level records, Model quantization for lower-precision deployment, and Model evaluation for workload evidence.

r2Seed corpus update
+1 / −1 words

As of 2026-07-13

Llama is Meta's downloadable model family distributed under release-specific community licenses. Open weights describe access to parameters; they do not by themselves establish an OSI-approved open-source license.

Revision snapshot

Llama is Meta's downloadable model family distributed under release-specific community licenses.

Open weights describe access to parameters; they do not by themselves establish an OSI-approved open-source license.

Why it matters: Llama model family is best understood as part of a system, not as a label in isolation. The practical questions are what inputs it accepts, what outputs it produces, which evidence supports its capabilities, what constraints surround deployment, and how those details change over time. The Compendium separates the documented facts above from interpretation and records an as-of date so readers can re-check the primary source.

Reading note: this is original explanatory writing. It links to the cited source instead of reproducing protected text. Product availability, model names, pricing, and policies can change; follow the source for the provider's current position.

r1Seed corpus update

As of 2026-07-13

Llama is Meta's downloadable model family distributed under release-specific community licenses. Open weights describe access to parameters; they do not by themselves establish an OSI-approved open-source license.

Revision snapshot

Llama is Meta's downloadable model family distributed under release-specific community licenses.

Open weights describe access to parameters; they do not by themselves establish an OSI-approved open-source license.

Why it matters: Llama model family is best understood as part of a system, not as a label in isolation. The practical questions are what inputs it accepts, what outputs it produces, which evidence supports its capabilities, what constraints surround deployment, and how those details change over time. The Atlas separates the documented facts above from interpretation and records an as-of date so readers can re-check the primary source.

Reading note: this is original explanatory writing. It links to the cited source instead of reproducing protected text. Product availability, model names, pricing, and policies can change; follow the source for the provider's current position.