Aikido Security Releases Altar-1: An Open-Weight Security Model Pruned From GLM-5.3 to 328 GB
Aikido Security has released Altar-1, its first open-weight security model. It is a compressed version of Z.AI’s GLM-5.3, built to run inside infrastructure the customer controls. Altar-1 powers Aikido Machine, the company’s autonomous pentesting appliance for on-prem and air-gapped networks. Is it deployable? Yes, the weights are public on Hugging Face and run with vLLM on a single node of 4x NVIDIA H200 GPUs. The Problem: Security Context Cannot Leave the Network Closed
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Aikido Security released Altar-1, a compressed security model derived from a larger model by removing unused components and reducing precision. The model was built to address a core problem: organizations under data-residency rules or operating air-gapped networks cannot send sensitive code and security findings to external AI services, yet existing open models are too large to run locally. Altar-1 achieves a 78 percent size reduction through two compression techniques: converting weights to lower precision and removing expert components that contributed least to performance, allowing it to run on a single node of four high-end GPUs. In vulnerability detection tests, the compressed model retained 92 percent of the original model's coverage while losing about 5 percentage points of recall.
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