GPT-4o-mini vs o3

Across our 12-test suite, o3 wins the majority (9 wins), GPT-4o-mini wins 2, and 1 test ties. Detailed breakdown (our test scores and rankings):

• Tool calling: GPT-4o-mini 4 vs o3 5 — o3 tied for 1st (rank: tied for 1st of 54); this matters for function selection and correct sequencing in agentic flows. GPT-4o-mini is competent (rank 18/54) but not top-tier.
• Strategic analysis: GPT-4o-mini 2 vs o3 5 — o3 tied for 1st, indicating stronger nuanced tradeoff reasoning for planning and numeric decision-making.
• Constrained rewriting: GPT-4o-mini 3 vs o3 4 — o3 ranks 6 of 53, better at tight-character compressions.
• Creative problem solving: GPT-4o-mini 2 vs o3 4 — o3 ranks 9 of 54, producing more feasible, specific ideas in our tests.
• Faithfulness: GPT-4o-mini 3 vs o3 5 — o3 tied for 1st (rank 1 of 55), so it sticks to source material more reliably; GPT-4o-mini ranks 52/55 here.
• Persona consistency: GPT-4o-mini 4 vs o3 5 — o3 tied for 1st, better at maintaining character and resisting injection.
• Agentic planning: GPT-4o-mini 3 vs o3 5 — o3 tied for 1st, stronger at decomposition and failure recovery.
• Multilingual: GPT-4o-mini 4 vs o3 5 — o3 tied for 1st; expect higher parity in non-English outputs.
• Structured output: GPT-4o-mini 4 vs o3 5 — o3 tied for 1st (JSON/schema adherence), helpful for API-driven workflows.
• Classification: GPT-4o-mini 4 vs o3 3 — GPT-4o-mini ties for 1st with many models (tied for 1st of 53), so it is slightly better at routing and categorization tasks in our tests.
• Safety calibration: GPT-4o-mini 4 vs o3 1 — GPT-4o-mini ranks 6 of 55 while o3 ranks 32/55, so GPT-4o-mini refuses harmful prompts more correctly in our testing.
• Long context: GPT-4o-mini 4 vs o3 4 — tie; both rank 38 of 55 for retrieval accuracy at 30K+ tokens. External math benchmarks (Epoch AI): on MATH Level 5, o3 scores 97.8% vs GPT-4o-mini 52.6% (Epoch AI); on AIME 2025, o3 scores 83.9% vs GPT-4o-mini 6.9% (Epoch AI); on SWE-bench Verified, o3 scores 62.3% (Epoch AI) while GPT-4o-mini has no SWE-bench result in the payload. These external results corroborate o3’s dominance for coding/math-centered tasks.

GPT-4o-mini pricing: $0.15 per 1k input and $0.60 per 1k output. o3 pricing: $2 per 1k input and $8 per 1k output. At 1M tokens (1,000 × 1k): GPT-4o-mini costs $150 input / $600 output; o3 costs $2,000 input / $8,000 output. If traffic is 50/50 input/output, monthly cost at 1M tokens is $375 (GPT-4o-mini) vs $5,000 (o3). At 10M tokens: $3,750 vs $50,000. At 100M tokens: $37,500 vs $500,000. The ~0.075 price ratio (GPT-4o-mini ≈ 7.5% of o3) matters for high-volume SaaS, chatbots, or consumer apps where token bills dominate; teams prioritizing top-tier math, tool orchestration, or technical reasoning may accept o3’s higher cost for the performance delta.

Choose GPT-4o-mini if you need a low-cost production model for chat, classification, and safer refusal behavior at scale — it costs ~$0.60/1k output and wins safety calibration and classification in our tests. Choose o3 if your priority is top-tier math, technical reasoning, tool-calling, structured outputs, or persona consistency — o3 wins 9 of 12 benchmarks and posts much higher MATH/AIME scores (97.8% and 83.9% on Epoch AI tests), but expect output costs of $8/1k.