R1 0528 vs GPT-5.4 for Safety Calibration

What Safety Calibration demands: refusing harmful requests while permitting legitimate ones. Key capabilities that matter are: consistent refusal logic, fine-grained policy judgement on borderline prompts, reliable structured outputs for policy hooks, and the ability to route or call mitigations (tool calling) for safe handling. In our testing the primary signal is the safety_calibration score: GPT-5.4 scored 5 vs R1 0528's 4. Supporting internal signals explain why: GPT-5.4 also scores 5 on structured_output and 5 on strategic_analysis in our tests, which helps it emit policy-compliant formats and reason about nuanced tradeoffs when deciding to refuse. R1 0528 scores 5 on tool_calling and 5 on faithfulness, indicating strong tool selection and adherence to source constraints, but it has a documented quirk — it returns empty responses on structured_output and requires high max completion tokens — which can weaken policy-hook workflows that rely on structured refusals.

1. Borderline violent request: GPT-5.4 (5) is more likely in our testing to produce a compliant refusal with an explicable rationale and structured signal (structured_output 5), reducing downstream moderation work. R1 0528 (4) will often refuse correctly but may lack the same structured policy output and can produce terse reasoning tokens that consume budget. 2) Regulatory or audit use where you must emit a machine-readable refusal: GPT-5.4's structured_output 5 (vs R1's 4) makes it a safer default in our benchmarks; R1's documented empty_on_structured_output quirk can cause missing JSON hooks. 3) Tool-mediated mitigation: R1 0528 scores 5 on tool_calling vs GPT-5.4's 4, so in our testing R1 is better at selecting and sequencing tools (e.g., calling a safety filter then a redaction tool) when you architect the pipeline to rely on tool calls. 4) Cost-sensitive, high-volume deployments: R1 0528 output cost is $2.15 per mTok vs GPT-5.4 at $15 per mTok in our data — R1 is ~7x cheaper on output tokens, which matters if you plan frequent safety-check generations or long justifications.

For Safety Calibration, choose R1 0528 if you need lower cost (R1 output $2.15/mTok vs GPT-5.4 $15/mTok), strong tool calling (R1 tool_calling 5 vs GPT-5.4 4), and you can work around R1's structured_output quirks. Choose GPT-5.4 if you need the most consistent refusal behavior and structured policy signals (GPT-5.4 scores 5 vs R1 0528's 4 on Safety Calibration in our testing and is ranked tied for 1st).