System1 Models — third-party notices Operated by productivity-boost.com Betriebs UG (haftungsbeschränkt) & Co. KG, Passau, Germany. Last updated: 2026-09-27 System1 Models serves the following third-party models through its API. Each is licensed under the Apache License, Version 2.0 (https://www.apache.org/licenses/LICENSE-2.0), unless stated otherwise. Model weights are used from the pinned revisions below; any format conversion or quantisation we apply is stated in the model card at /models. ================================================================================ s1-fast = Plumb-4B (https://huggingface.co/crh225/plumb-4b) revision 55de037801a8a9b9de3db5c0e16cef86210c2186 (engine pin) -------------------------------------------------------------------------------- jevy (Plumb-4B) Copyright 2026 Christopher House This product includes software and model weights developed by others: - JevK5 v0.2 (starting weights, training scripts, runtime and JevBench adapter), by the JevK5 authors (github.com/allebee, huggingface.co/alibiserikbay), Apache License 2.0. Its own notice is kept in NOTICE-jevk5. - Qwen3.5-4B (base weights) and Qwen3.8-27B (teacher), by the Qwen team, Apache License 2.0. - The decision prompt and the one-pass readout, adapted by JevK5 from SemIf by TheoLeeCJ (https://github.com/TheoLeeCJ/SemIf), MIT License. - Public datasets used as replay (MNLI, WANLI, BoolQ, banking77, ARC, CommonsenseQA, MMLU-Pro), under their own licences. --- NOTICE-jevk5 (included by Plumb-4B) --- JevK5 Copyright 2026 the JevK5 authors (github.com/allebee, huggingface.co/alibiserikbay) This product includes software and model weights developed by others: - Qwen3.5-4B (base weights) and Qwen3.6-27B (teacher), by the Qwen team, Apache License 2.0. - The decision prompt (system instruction and JSON payload of evidence, criterion and lettered options) and the one-pass readout (softmax over the answer letters' next-token logits) are adapted from SemIf by TheoLeeCJ (https://github.com/TheoLeeCJ/SemIf), MIT License: Copyright (c) TheoLeeCJ Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND. - Training replay data from MMLU-Pro (MIT), WANLI (CC BY 4.0), MultiNLI, BoolQ (CC BY-SA 3.0), banking77 (CC BY 4.0), ARC (CC BY-SA 4.0) and CommonsenseQA (MIT), under their own licenses. Base model Qwen3.5-4B (https://huggingface.co/Qwen/Qwen3.5-4B), Copyright the Qwen team, Alibaba Cloud, Apache License 2.0. ================================================================================ s1-pro = Winnow-12B (https://huggingface.co/EldanRing/Winnow-12B) revision b2b14213dfa252e6d6b543c8b334762e51772d29 (engine pin; NOTICE text below as published by the author at the later revision b6ac22b0, same licence) -------------------------------------------------------------------------------- Winnow-12B Base model: Gemma 4 12B IT by Google DeepMind Source: https://huggingface.co/google/gemma-4-12B-it Source revision: 707f0a3b8a3c7ad586ed01e27eafbad8a27dd0f7 Upstream license: Apache License, Version 2.0 License reference: https://ai.google.dev/gemma/docs/gemma_4_license Winnow modifications are developed by EldanRing. The released model weights modify the base through task-specific LoRA fine-tuning and adapter merging. The Q8_0 GGUF is converted and quantized from those merged weights. Configuration and weight sharding were updated during export; tokenizer and chat template assets were preserved. The matching vision projector is unchanged by the decision fine-tuning. Artifact hashes are recorded in SHA256SUMS and release-manifest.json. This file records Winnow's attribution and modifications. It does not imply that the upstream model distribution supplied a NOTICE file. The separate Winnow inference code builds on llama.cpp by Georgi Gerganov and contributors under the MIT license. Its repository contains the applicable copyright and license text. No llama.cpp source or binary is included here. Winnow is an independent project; no upstream endorsement is implied. Gemma 4 12B IT, Copyright Google LLC / Google DeepMind, Apache License 2.0 (https://ai.google.dev/gemma/docs/gemma_4_license). Gemma is a trademark of Google LLC. ================================================================================ s1-vision = Jev-Omni (https://huggingface.co/akhilaaa3/Jev-Omni) [only if offered] revision 5addda86ddee081a68fb067477ea100c221b8917 -------------------------------------------------------------------------------- Jev-Omni by akhilaaa3. Licence: Apache-2.0 as declared by the author in the model card (the repository contains no separate LICENSE or NOTICE file). Built on Gemma 4 12B IT, Copyright Google LLC / Google DeepMind, Apache License 2.0. ================================================================================ Trademarks: "Jev" is a trademark of TypeSafe AI. 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