Sovereign Mamba is a state-space model (SSM) designed to operate entirely on local hardware without reliance on cloud services. Developed as a sovereign open-source variant by SnapKitty Collective, it is architected with 32 layers and a model dimension of 4096, and features compatibility with the Nemotron-3-8B weight layout. 1.
Distinctively, Sovereign Mamba does not use attention mechanisms, instead relying on a pure SSM approach, which enables O(n) inference complexity compared to the O(n^2) complexity typical of transformer models. This design choice supports efficient inference, particularly for structured prediction tasks. The model incorporates a Watson CRF to Mamba SSM bridge for structured prediction, and employs the ERRANT-GGML linear-typed tensor resource system, which is described as Prolog-proven for tensor flow.
0. While the codebase is accessible, commercial use requires a trust agreement with THE SHARED PRIMORDIAL FOUNDATION (EIN 42-6976431). com/SNAPKITTYWEST/foundry-f1.
This tool is suitable for those seeking a state-space model that can be run locally, particularly on compatible NVIDIA hardware, and who require efficient structured prediction capabilities without cloud dependency. Its licensing terms make it available for non-commercial use, with commercial use subject to specific agreement.
Sovereign Mamba sits in PulseGate's Foundation models & chat category. It focuses on providing a locally runnable, constitutionally aligned AI model for structured prediction and reasoning without cloud dependency. Sovereign Mamba is an open-source project aimed at AI researchers and developers. The project is open source (Open Source). Sovereign Mamba is available on the web, API, and the command line, and it can be self-hosted.
It is developed by SnapKitty Collective / THE SHARED PRIMORDIAL FOUNDATION, and the product first shipped in 2026. The project is developed in the open on GitHub with 75 commits in the last 90 days. Across PulseGate's embedding index, Sovereign Mamba has few near neighbours, marking it as relatively distinct. Among its 5 catalogued features are state-space modeling, local inference, and nemotron compatibility.
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