GPT-4o-mini vs GPT-5

Summary of our 12-test comparison (scores and ranks come from our testing and the payload):

• Wins by GPT-5 (10 categories): structured output 5 vs 4 (GPT-5 tied for 1st of 54; GPT-4o-mini rank 26 of 54). Strategic_analysis 5 vs 2 (GPT-5 tied for 1st; GPT-4o-mini rank 44 of 54). Constrained_rewriting 4 vs 3 (GPT-5 rank 6 of 53; GPT-4o-mini rank 31 of 53). Creative_problem_solving 4 vs 2 (GPT-5 rank 9 of 54; GPT-4o-mini rank 47 of 54). Tool_calling 5 vs 4 (GPT-5 tied for 1st of 54; GPT-4o-mini rank 18 of 54). Faithfulness 5 vs 3 (GPT-5 tied for 1st of 55; GPT-4o-mini rank 52 of 55). Long_context 5 vs 4 (GPT-5 tied for 1st of 55; GPT-4o-mini rank 38 of 55). Persona_consistency 5 vs 4 (GPT-5 tied for 1st of 53; GPT-4o-mini rank 38 of 53). Agentic_planning 5 vs 3 (GPT-5 tied for 1st of 54; GPT-4o-mini rank 42 of 54). Multilingual 5 vs 4 (GPT-5 tied for 1st of 55; GPT-4o-mini rank 36 of 55).
• GPT-4o-mini wins: safety calibration 4 vs GPT-5's 2 (GPT-4o-mini rank 6 of 55; GPT-5 rank 12 of 55). This indicates GPT-4o-mini is more likely to refuse harmful requests and better balance permission vs refusal in our safety tests.
• Tie: classification (both score 4) — both models are tied for 1st among tested models for classification tasks in our data. External benchmarks (Epoch AI) supplement these results: GPT-5 scores 73.6% on SWE-bench Verified (Epoch AI) and ranks 6 of 12 on that coding benchmark; GPT-5 scores 98.1% on MATH Level 5 (rank 1 of 14) and 91.4% on AIME 2025 (rank 6 of 23). GPT-4o-mini's external math scores are lower in our payload: MATH Level 5 52.6% (rank 13 of 14) and AIME 2025 6.9% (rank 21 of 23). These external scores corroborate GPT-5's large advantage on math and coding reasoning in our evaluation. Practical meaning: choose GPT-5 for complex step-by-step reasoning, agentic planning, tool-calling workflows, long-context retrieval (GPT-5 tied for 1st in long context and has a 400k context window vs GPT-4o-mini's 128k window). Choose GPT-4o-mini when safety calibration and dramatically lower costs are your priority.

Pricing per 1k (mtok) from the payload: GPT-4o-mini input $0.15 / output $0.60; GPT-5 input $1.25 / output $10.00. Example costs assuming a 50/50 split of input/output tokens (1M total tokens = 500k input + 500k output): GPT-4o-mini ≈ $375 per 1M tokens (500 mtok * $0.15 + 500 mtok * $0.60); GPT-5 ≈ $5,625 per 1M tokens (500 mtok * $1.25 + 500 mtok * $10.00). Scaling: at 10M tokens/month multiply those numbers by 10 (GPT-4o-mini $3,750; GPT-5 $56,250); at 100M multiply by 100 (GPT-4o-mini $37,500; GPT-5 $562,500). If you measure output-heavy workloads, cost per 1M output tokens alone is $600 (GPT-4o-mini) vs $10,000 (GPT-5). The payload's priceRatio (0.06) reflects that GPT-4o-mini's per-token pricing is ~6% of GPT-5's in the dominant output cost. Who should care: small teams, high-volume SaaS, and hobbyists will prefer GPT-4o-mini for cost control; enterprises or teams needing top-tier reasoning, code quality, or math performance may justify GPT-5's much higher bill.

Choose GPT-4o-mini if: you must minimize per-token costs (output $0.60 / 1k vs $10 for GPT-5), need stronger safety calibration in our tests, or want a capable multimodal model with up to 128k context for cost-sensitive production apps. Choose GPT-5 if: you prioritize the best reasoning, coding, agentic planning, tool-calling, and long-context performance (GPT-5 wins 10 of 12 benchmarks and scores much higher on external math and coding tests), and you can afford the much higher bill and larger 400k context window.