{
  "schema_version": "rangoon.article.v1",
  "id": "https://rangoon.ai/insights/archive-llama-3-3-70b-2024/",
  "url": "https://rangoon.ai/insights/archive-llama-3-3-70b-2024/",
  "markdown_url": "https://rangoon.ai/insights/archive-llama-3-3-70b-2024/index.md",
  "json_url": "https://rangoon.ai/insights/archive-llama-3-3-70b-2024/index.json",
  "title": "Llama 3.3’s 70B release made license and benchmark context part of adoption",
  "summary": "Meta released Llama 3.3 70B Instruct on December 6, 2024. Open weights, a model card, and vendor evaluations each answer different adoption questions.",
  "language": "en",
  "author": {
    "name": "Rangoon Editorial",
    "url": "https://rangoon.ai/insights/editorial/"
  },
  "publisher": {
    "name": "Rangoon",
    "maintainer": "Hypler",
    "url": "https://rangoon.ai/"
  },
  "format": "News analysis",
  "topic": {
    "slug": "models",
    "label": "Models",
    "url": "https://rangoon.ai/insights/topics/models/"
  },
  "tags": [
    {
      "slug": "meta",
      "label": "Meta",
      "url": "https://rangoon.ai/insights/tags/meta/"
    },
    {
      "slug": "llama-3-3",
      "label": "Llama 3.3",
      "url": "https://rangoon.ai/insights/tags/llama-3-3/"
    },
    {
      "slug": "open-weights",
      "label": "open weights",
      "url": "https://rangoon.ai/insights/tags/open-weights/"
    },
    {
      "slug": "model-card",
      "label": "model card",
      "url": "https://rangoon.ai/insights/tags/model-card/"
    }
  ],
  "dates": {
    "published": "2026-10-23",
    "updated": "2026-10-23",
    "event": "2024-12-06"
  },
  "event_source_id": 1,
  "retrospective": true,
  "reading_minutes": 3,
  "takeaways": [
    "The official Llama 3.3 70B Instruct model card records a December 6, 2024 release date.",
    "Before adoption, pin the exact model identifier and revision, then review the applicable license and acceptable-use terms against the planned distribution, modification, hosting, and user flow.",
    "The December 2024 materials support Meta’s stated Llama 3.3 release. They do not establish current availability, legal interpretation, or local benchmark performance."
  ],
  "source_note": "Historical reporting: The December 6, 2024 Llama 3.3 70B Instruct model card records the artifact; Meta’s December 19 retrospective is a distinct primary account of the release. The analysis below is original editorial analysis; it does not claim present availability, performance, or support.",
  "sources": [
    {
      "id": 1,
      "title": "Llama 3.3 70B Instruct model card",
      "url": "https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct",
      "published": "2024-12-06"
    },
    {
      "id": 2,
      "title": "Meta AI: The future of AI, built with Llama",
      "url": "https://ai.meta.com/blog/future-of-ai-built-with-llama",
      "published": null
    }
  ],
  "image": {
    "url": "https://rangoon.ai/assets/editorial/archive-llama-3-3-70b-2024-diagram-v1.webp",
    "thumbnail_url": "https://rangoon.ai/assets/editorial/archive-llama-3-3-70b-2024-diagram-v1-thumb.webp",
    "alt": "Original models review diagram: Llama 3.3 model-card scope. Concepts: model artifact, license terms, runtime format, evaluation harness, provenance ledger. Editorial checklist, not vendor test results or an official legal determination.",
    "type": "original-diagram",
    "caption": "Llama 3.3 model-card scope. Original Rangoon explanatory diagram: concepts for editorial review, not measured results, an official legal determination, vendor interface or event photograph.",
    "credit": "Rangoon / Hypler",
    "source_url": "https://rangoon.ai/brand/",
    "rights_url": "https://rangoon.ai/terms/#media-use",
    "rights_note": "Hypler artwork permissions do not grant rights to third-party marks or imply endorsement."
  },
  "sections": [
    {
      "id": "event",
      "url": "https://rangoon.ai/insights/archive-llama-3-3-70b-2024/#event",
      "heading": "What Meta released",
      "paragraphs": [
        "The official Llama 3.3 70B Instruct model card records a December 6, 2024 release date. Meta’s December 19 retrospective lists the 70B Instruct model among its late-2024 releases and discusses vendor-reported comparisons. The artifact, license terms, and benchmark conditions are related, but each must be examined directly.",
        "The Llama 3.3 70B Instruct model card is a separate primary document that describes the artifact, intended use, limitations, and license reference. A model card is not a serving benchmark, and a benchmark table is not a legal approval for a particular product use. Its declared intended-use boundaries also deserve review against the planned user task."
      ],
      "bullets": [],
      "source_ids": [
        1,
        2
      ]
    },
    {
      "id": "operating-question",
      "url": "https://rangoon.ai/insights/archive-llama-3-3-70b-2024/#operating-question",
      "heading": "Editorial analysis: review the artifact and license together",
      "paragraphs": [
        "Before adoption, pin the exact model identifier and revision, then review the applicable license and acceptable-use terms against the planned distribution, modification, hosting, and user flow. Record the reviewer, decision, and any constraints rather than relying on a family-level memory of ‘open.’",
        "Treat every conversion or quantization as a new artifact in the operating record. It may preserve weights semantically while changing performance, memory needs, tokenizer packaging, or provenance details needed for incident response."
      ],
      "bullets": [],
      "source_ids": []
    },
    {
      "id": "evaluation-boundary",
      "url": "https://rangoon.ai/insights/archive-llama-3-3-70b-2024/#evaluation-boundary",
      "heading": "Editorial analysis: preserve supplier benchmark conditions",
      "paragraphs": [
        "A vendor comparison should keep the task set, prompt method, few-shot policy, decoding, and score definition next to the result. If a local test uses another harness, present it as a different measurement rather than an attempted replica.",
        "For multilingual workloads, evaluate each required language and format. A broad language list does not establish quality on domain terminology, regional variants, structured extraction, or user-supplied mixed-language documents."
      ],
      "bullets": [],
      "source_ids": []
    },
    {
      "id": "decision-record",
      "url": "https://rangoon.ai/insights/archive-llama-3-3-70b-2024/#decision-record",
      "heading": "Editorial analysis: make deployment provenance inspectable",
      "paragraphs": [
        "Maintain a model bill of materials: base artifact, revision, conversion, quantization, runtime, prompt template, tools, license review, and fixture report. The record gives a later maintainer a route from an output to the exact technical and legal inputs.",
        "Meta’s release date is a bounded historical claim. Current distribution channels, platform policies, and derivative artifacts require fresh evidence instead of being inferred from December 2024."
      ],
      "bullets": [],
      "source_ids": []
    },
    {
      "id": "historical-limit",
      "url": "https://rangoon.ai/insights/archive-llama-3-3-70b-2024/#historical-limit",
      "heading": "Editorial analysis: retain the release boundary",
      "paragraphs": [
        "The December 2024 materials support Meta’s stated Llama 3.3 release. They do not establish current availability, legal interpretation, or local benchmark performance.",
        "A model bill of materials should survive handoff. Imagine a team receives a quantized derivative from an internal artifact store months after the base release. Without the original model identifier, conversion command, checksum, license review, runtime, and prompt template, it cannot tell whether a quality or legal change came from Meta’s release, the conversion, or the application. Require the derivative to point back to its base and test report. For a multilingual use case, retain the language-specific fixtures that justified adoption. This is an operational provenance example, not legal advice and not a claim about any particular Llama derivative.",
        "Provenance should include the date an organization obtained each artifact. That prevents a later download or repackaging from being mistakenly described as the original December release."
      ],
      "bullets": [],
      "source_ids": []
    }
  ],
  "project_context": null,
  "related_links": [],
  "permissions_url": "https://rangoon.ai/permissions.txt",
  "content_hash": "sha256:ea4c74c4cc55e7763a046973cdddac277353967936817c7a7a93b7bd8c5d41e9"
}