{"schema":"record/v1","id":"art_01M5NCHQGF802JBQ36VKC1G1T4","type":"article","revision":1,"etag":"\"r1.s0\"","title":"What do the InsightFace repositories say about the licence of buffalo_l, antelopev2 and other pretrained models versus the MIT-licensed library, and who must be contacted for commercial use?","summary":"Problem. IPAdapter FaceID, face swap and portrait nodes in ComfyUI depend on insightface models. Conditions. deepinsight/insightface commit c6c3af7b (2026-10-19). Cross-checks an earlier round's licence item without repeating it. Method. The main README states the code is MIT with no limit on academic or commercial use, but training data with annotations 'and the models trained with these data' are for non-commercial research only, and this applies both to manual downloads and to auto-downloads through the Python library. It lists contacts for licensing: inswapper-series face swap models (inswapper_128.onnx etc.), the open-sourced face recognition packages such as buffalo_l (a separate recognition-oss-pack contact), and the InspireFace SDK. The model_zoo README opens with 'ALL models are available for non-commercial research purposes only'; the python-package README repeats that the pretrained models are non-commercial research only, whether downloaded automatically or manually, and...","status":"active","body":{"text":"Problem. IPAdapter FaceID, face swap and portrait nodes in ComfyUI depend on insightface models. Conditions. deepinsight/insightface commit c6c3af7b (2026-10-19). Cross-checks an earlier round's licence item without repeating it. Method. The main README states the code is MIT with no limit on academic or commercial use, but training data with annotations 'and the models trained with these data' are for non-commercial research only, and this applies both to manual downloads and to auto-downloads through the Python library. It lists contacts for licensing: inswapper-series face swap models (inswapper_128.onnx etc.), the open-sourced face recognition packages such as buffalo_l (a separate recognition-oss-pack contact), and the InspireFace SDK. The model_zoo README opens with 'ALL models are available for non-commercial research purposes only'; the python-package README repeats that the pretrained models are non-commercial research only, whether downloaded automatically or manually, and that model licences apply separately from the library's MIT licence. antelopev2 is not named in these three files by my search; it is distributed by the same project, so the same policy statement is the closest source (inference), and ComfyUI IPAdapter notes users must download it manually (round 2). Failure modes. Treating the MIT library licence as covering the bundled/auto-downloaded models; auto-download in a CI or production container. Limitations. Terms for specific third-party mirrors of the models (Hugging Face reuploads) not read. Not legal advice; a reading of published text for engineering triage. Version and date. Commit c6c3af7b.\n\nCurator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources.\n\nLimitations: antelopev2 coverage by inference.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://raw.githubusercontent.com/deepinsight/insightface/c6c3af7bd2d0a0bf4b78c78437357f3521aa5d52/model_zoo/README.md","note":"top of README; License; License point 2"},{"url":"https://raw.githubusercontent.com/deepinsight/insightface/c6c3af7bd2d0a0bf4b78c78437357f3521aa5d52/python-package/README.md","note":"top of README; License; License point 2"},{"url":"https://raw.githubusercontent.com/deepinsight/insightface/c6c3af7bd2d0a0bf4b78c78437357f3521aa5d52/README.md","note":"top of README; License; License point 2"}]},"categories":["T05","T09","T20"],"tags":[],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"source_inspected","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[{"url":"https://raw.githubusercontent.com/deepinsight/insightface/c6c3af7bd2d0a0bf4b78c78437357f3521aa5d52/model_zoo/README.md","claim":"Problem. IPAdapter FaceID, face swap and portrait nodes in ComfyUI depend on insightface models. Conditions. deepinsight/insightface commit c6c3af7b (2026-10-19). Cross-checks an earlier round's licence item without repeating it. Method. The main README states the code is MIT with no limit on academic or commercial use, but training data with annotations 'and the models trained with these data' are for non-commercial research only, and this applies both to manual downloads and to auto-downloads through the Python library. It lists contacts for licensing: inswapper-series face swap models (inswapper_128.onnx etc.), the open-sourced face recognition packages such as buffalo_l (a separate recognition-oss-pack contact), and the InspireFace SDK. The model_zoo README opens with 'ALL models are available for non-commercial research purposes only'; the python-package README repeats that the pretrained models are non-commercial research only, whether downloaded automatically or manually, and that model licences apply separately from the library's MIT licence. antelopev2 is not named in these three files by my search; it is distributed by the same project, so the same policy statement is the closest source (inference), and ComfyUI IPAdapter notes users must download it manually (round 2). Failure modes. Treating the MIT library licence as covering the bundled/auto-downloaded models; auto-download in a CI or production container. Limitations. Terms for specific third-party mirrors of the models (Hugging Face reuploads) not read. Not legal advice; a reading of published text for engineering triage. Version and date. 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IPAdapter FaceID, face swap and portrait nodes in ComfyUI depend on insightface models. Conditions. deepinsight/insightface commit c6c3af7b (2026-10-19). Cross-checks an earlier round's licence item without repeating it. Method. The main README states the code is MIT with no limit on academic or commercial use, but training data with annotations 'and the models trained with these data' are for non-commercial research only, and this applies both to manual downloads and to auto-downloads through the Python library. It lists contacts for licensing: inswapper-series face swap models (inswapper_128.onnx etc.), the open-sourced face recognition packages such as buffalo_l (a separate recognition-oss-pack contact), and the InspireFace SDK. The model_zoo README opens with 'ALL models are available for non-commercial research purposes only'; the python-package README repeats that the pretrained models are non-commercial research only, whether downloaded automatically or manually, and that model licences apply separately from the library's MIT licence. antelopev2 is not named in these three files by my search; it is distributed by the same project, so the same policy statement is the closest source (inference), and ComfyUI IPAdapter notes users must download it manually (round 2). Failure modes. Treating the MIT library licence as covering the bundled/auto-downloaded models; auto-download in a CI or production container. Limitations. Terms for specific third-party mirrors of the models (Hugging Face reuploads) not read. Not legal advice; a reading of published text for engineering triage. Version and date. Commit c6c3af7b.\n\nCurator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources.\n\nLimitations: antelopev2 coverage by inference.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://raw.githubusercontent.com/deepinsight/insightface/c6c3af7bd2d0a0bf4b78c78437357f3521aa5d52/model_zoo/README.md","note":"top of README; License; License point 2"},{"url":"https://raw.githubusercontent.com/deepinsight/insightface/c6c3af7bd2d0a0bf4b78c78437357f3521aa5d52/python-package/README.md","note":"top of README; License; License point 2"},{"url":"https://raw.githubusercontent.com/deepinsight/insightface/c6c3af7bd2d0a0bf4b78c78437357f3521aa5d52/README.md","note":"top of README; License; License point 2"}]},"tags":[],"type":"article","links":[],"title":"What do the InsightFace repositories say about the licence of buffalo_l, antelopev2 and other pretrained models versus the MIT-licensed library, and who must be contacted for commercial use?","rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"summary":"Problem. IPAdapter FaceID, face swap and portrait nodes in ComfyUI depend on insightface models. Conditions. deepinsight/insightface commit c6c3af7b (2026-10-19). Cross-checks an earlier round's licence item without repeating it. Method. The main README states the code is MIT with no limit on academic or commercial use, but training data with annotations 'and the models trained with these data' are for non-commercial research only, and this applies both to manual downloads and to auto-downloads through the Python library. It lists contacts for licensing: inswapper-series face swap models (inswapper_128.onnx etc.), the open-sourced face recognition packages such as buffalo_l (a separate recognition-oss-pack contact), and the InspireFace SDK. The model_zoo README opens with 'ALL models are available for non-commercial research purposes only'; the python-package README repeats that the pretrained models are non-commercial research only, whether downloaded automatically or manually, and...","evidence":{"claims":[{"url":"https://raw.githubusercontent.com/deepinsight/insightface/c6c3af7bd2d0a0bf4b78c78437357f3521aa5d52/model_zoo/README.md","claim":"Problem. IPAdapter FaceID, face swap and portrait nodes in ComfyUI depend on insightface models. Conditions. deepinsight/insightface commit c6c3af7b (2026-10-19). Cross-checks an earlier round's licence item without repeating it. Method. The main README states the code is MIT with no limit on academic or commercial use, but training data with annotations 'and the models trained with these data' are for non-commercial research only, and this applies both to manual downloads and to auto-downloads through the Python library. It lists contacts for licensing: inswapper-series face swap models (inswapper_128.onnx etc.), the open-sourced face recognition packages such as buffalo_l (a separate recognition-oss-pack contact), and the InspireFace SDK. The model_zoo README opens with 'ALL models are available for non-commercial research purposes only'; the python-package README repeats that the pretrained models are non-commercial research only, whether downloaded automatically or manually, and that model licences apply separately from the library's MIT licence. antelopev2 is not named in these three files by my search; it is distributed by the same project, so the same policy statement is the closest source (inference), and ComfyUI IPAdapter notes users must download it manually (round 2). Failure modes. Treating the MIT library licence as covering the bundled/auto-downloaded models; auto-download in a CI or production container. Limitations. 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