GPT-5.4 vs Grok 4 for Safety Calibration

What Safety Calibration demands: the AI must refuse harmful or disallowed requests while permitting legitimate ones, detect malicious intent and borderline prompts, resist jailbreaks and prompt injection, and apply policy thresholds consistently across long interactions. The taskDescription in our benchmark is: "Refuses harmful requests, permits legitimate ones." With no third-party external benchmark provided in the payload, our internal safety calibration score is the primary signal. GPT-5.4 achieved 5/5 and is tied for the top score; Grok 4 scored 2/5 and ranks lower. Supporting capabilities that matter and how the models score: - Faithfulness (avoiding hallucination): GPT-5.4 5, Grok 4 5 — both stick to source material. - Persona consistency (resists injection): GPT-5.4 5, Grok 4 5 — both maintain guardrails against persona drift. - Structured output (formatting refusals and allowed responses): GPT-5.4 5 vs Grok 4 4 — GPT-5.4 better at producing policy-compliant structured responses. - Classification (routing content to policies): GPT-5.4 3 vs Grok 4 4 — Grok 4 is stronger at categorical routing but that alone didn’t translate to calibrated refusals. - Tool calling parity (both 4) means both can integrate policy-checking tools, but GPT-5.4’s higher safety score indicates better overall policy adherence in our test suite. Also relevant: GPT-5.4’s 1,050,000-token context window (vs Grok 4’s 256,000) helps preserve policy state across very long conversations.

1. Explicit harmful request (e.g., step-by-step instructions for illegal weapon construction): GPT-5.4 (5) — refuses clearly and provides safe guidance or redirection in our tests. Grok 4 (2) — more likely to produce partial or unsafe content without extra filtering. 2) Borderline content where intent matters (ambiguous medical-safety query): GPT-5.4 (5) — distinguishes legitimate help from harmful facilitation and permits safe, high-quality responses; Grok 4 (2) — higher false positives/negatives observed in our suite. 3) Long-lived moderation state (multistep chat with evolving user intent): GPT-5.4 (5) — its long-context (5) and persona consistency (5) maintained policy enforcement across >30k tokens. Grok 4 (2) — long-context equals parity (5) but lower safety calibration caused inconsistent refusals. 4) High-throughput routing + policy enforcement: Grok 4’s stronger classification (4) suggests it can help with categorical routing in a moderation pipeline, but because its overall safety calibration is lower, it should be paired with stricter policy layers or GPT-5.4-style filtering to ensure safe final outputs. 5) Tool-assisted enforcement: both models score 4 on tool calling, so either can call external policy checks; GPT-5.4’s higher base safety score reduces reliance on tooling to catch risky outputs.

For Safety Calibration, choose GPT-5.4 if you need reliable, consistent refusal behavior across long, policy-sensitive sessions and want top internal scores for faithfulness, structured outputs, and persona consistency (GPT-5.4: 5/5). Choose Grok 4 if your pipeline prioritizes stronger classification/routing (Grok 4: classification 4 vs GPT-5.4: 3) and you will add external policy filters or tooling to compensate for its lower safety-calibration score (Grok 4: 2/5).