Gemini 2.5 Pro vs GPT-5.4 for Faithfulness

What Faithfulness demands: sticking to source material without inventing facts, citing or structuring evidence correctly, and refusing unsupported inferences. Capabilities that matter: long-context retrieval (for sourcing), structured_output (format and citation accuracy), tool_calling (function selection and correct argument use to retrieve or verify sources), safety_calibration (refusal/guardrail behavior that prevents plausible-sounding hallucinations), and multimodal input when sources include audio/video. External benchmarks are not available for this task in the payload, so our winner call relies on our internal test results. Both Gemini 2.5 Pro and GPT-5.4 scored 5/5 on Faithfulness and are tied for rank 1 in our faithfulness test across 52 models. Supporting signals diverge: both have long_context=5 and structured_output=5 (strong for fidelity), but Gemini has tool_calling=5 versus GPT-5.4's 4 (advantage for tool-backed verification and extraction), while GPT-5.4 has safety_calibration=5 versus Gemini's 1 (advantage for conservative refusal and lower hallucination risk). Also note modality differences in the data: Gemini 2.5 Pro supports text+image+file+audio+video->text, which can improve fidelity when working with non-text sources; GPT-5.4 supports text+image+file->text.

1. High-stakes policy or compliance text where hallucination must be minimized: GPT-5.4 is preferable because safety_calibration is 5 vs Gemini's 1, lowering the chance of producing unsupported claims. 2) Multi-document extraction with tool integration (e.g., call a retrieval API or run a structured query over documents): Gemini 2.5 Pro excels because tool_calling is 5 vs GPT-5.4's 4 and it supports audio/video sources, so it better handles tool-backed citations and multimodal evidence. 3) Producing exact JSON or schema-compliant citations: both models score structured_output=5, so either produces reliable structured outputs in our tests. 4) Long-context fidelity (30K+ tokens): both score long_context=5, so for very large documents both maintain retrieval accuracy equally well in our testing. 5) Cost-sensitive fidelity checks: Gemini has lower output cost (output_cost_per_mtok=10) versus GPT-5.4 (output_cost_per_mtok=15), so repeated tool-backed verification runs are cheaper on Gemini in our data.

For Faithfulness, choose Gemini 2.5 Pro if you need tool-backed extraction, multimodal source handling (audio/video), or lower output cost for repeated verification runs. Choose GPT-5.4 if you prioritize conservative, guardrail-driven responses that minimize unsupported claims — its safety_calibration advantage (5 vs 1 in our testing) gives it a narrow edge for high-risk or compliance-critical outputs.