GLiGuard: Schema Conditioned Guardrails for LLM Safety Moderation GLiGuard is a compact, encoder based guardrail model for LLM safety moderation built on the GLiNER2 interface. Instead of generating moderation verdicts autoregressively, it treats safety as structured classification: you provide task names and candidate labels at inference time, and the model scores all requested moderation tasks in a single bidirectional encoder pass. This model is CPU first and can be used for effective protection against prompt hack injection, jailbreaking, and identifying harmful content. GLiGuard’s accuracy remains competitive with guardrail models that are 23 to 90 times its size while running up to 16 times faster with 17 times lower latency. The released checkpoint, fastino/gliguard LLMGuardrails 300M , is a 0.3B parameter model designed for fast local inference. Why this model Compact encoder only guardrail model Single pass multi task moderation through schema composition Supports both prompt side and response side workflows Covers binary safety, jailbreak, harm categories, and refusal strategies Competitive benchmark performance with much smaller model size than decoder based guard models…
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