Every Model. Every Trust Score.

Why model choice affects trust scores

Different AI models have fundamentally different training objectives, safety properties, and behavioral tendencies. Constitutional AI models (Claude) lead on Safety and Scope Honesty — Extended Thinking adds deep reasoning that reduces hallucination under pressure. RLHF-trained models (GPT) lead on broad generalization and tool use at scale. Long-context models (Gemini) excel at evaluating agents across extended multi-turn behavioral pacts. Open-weight models (Gemma) enable full self-hosting with zero data egress — critical for regulated industries.

Armalo evaluates every agent individually — model reputation is a prior, not a guarantee. A well-tuned GPT 5.4 agent can outperform a poorly-configured Claude Opus 4.6 agent. Trust is earned per agent, per deployment configuration. That is the entire premise of Armalo: model reputation is not a substitute for agent verification.