Gemini 2.5 Pro vs GPT-5.4 for Constrained Rewriting

Constrained Rewriting (compression within hard character limits) demands: precise length control, preservation of key facts (faithfulness), adherence to output schemas or tokens (structured_output), and the ability to trade fidelity vs brevity (strategic_analysis). In our testing there is no external benchmark for this task, so we rely on internal task scores and related proxies. GPT-5.4 scores 4 on constrained_rewriting vs Gemini 2.5 Pro's 3; GPT-5.4 also scores higher on strategic_analysis (5 vs 4) and safety_calibration (5 vs 1), which help it make safer, clearer compressions when a rewrite must refuse or tightly edit content. Both models tie at 5 for structured_output and faithfulness, meaning they can follow schemas and generally preserve source facts. Gemini's strengths (tool_calling 5 vs 4, creative_problem_solving 5 vs 4) suggest it can produce inventive compressions and integrate tools, and its larger modality support may matter for multimodal inputs, but those do not offset GPT-5.4's advantage on the core compression tradeoffs in our constrained_rewriting test.

1. High-stakes microcopy: Compress a 1,200‑word privacy policy into a 280‑char compliance blurb. GPT-5.4 (score 4) is more likely in our tests to balance brevity and legal fidelity because it scores 5 on strategic_analysis and 5 on safety_calibration; Gemini 2.5 Pro (score 3) may produce shorter text but risks missing nuance. 2) Character-limited marketing SMS where creative phrasing matters: Gemini 2.5 Pro’s creative_problem_solving 5 and tool_calling 5 give it an edge for inventive shortcuts and integrating external token-count tools, and it costs less ($1.25 input / $10 output per mTok). 3) Multimodal caption compression: If you must compress video captions or transcribed audio, Gemini 2.5 Pro accepts audio/video inputs (modality includes audio+video) and is cost-efficient; expect more engineering flexibility even though its constrained_rewriting score is 3. 4) Schema-constrained API output: Both models tie at structured_output 5 and faithfulness 5, so for strict JSON-limited rewrites either will reliably meet format constraints; prefer GPT-5.4 when the primary goal is maximal information retention under a hard limit.

For Constrained Rewriting, choose Gemini 2.5 Pro if you need lower cost or multimodal input handling ($1.25 input / $10 output per mTok), or you want stronger creative compression and tool integration. Choose GPT-5.4 if you need the best hard-limit compression fidelity and safer tradeoffs — it scores 4 vs 3 on our constrained_rewriting test and ranks 6th vs 31st.