GPT-4o-mini vs o4 Mini

Overview (our internal 1–5 scores unless noted):

• Multilingual: GPT-4o-mini 4 vs o4 Mini 5 — o4 Mini ties for 1st (rank tied with 34 others), GPT-4o-mini ranks 36/55. This means o4 Mini is stronger for equivalent-quality non-English output.
• Creative problem solving: GPT-4o-mini 2 vs o4 Mini 4 — o4 Mini ranks 9/54 vs GPT-4o-mini rank 47/54; expect o4 Mini to produce more feasible, non-obvious ideas in our tests.
• Constrained rewriting: tie 3/3 — both perform similarly on tight-character compression.
• Faithfulness: GPT-4o-mini 3 vs o4 Mini 5 — o4 Mini is tied for 1st (stronger at sticking to source material; GPT-4o-mini ranks 52/55).
• Agentic planning: GPT-4o-mini 3 vs o4 Mini 4 — o4 Mini ranks 16/54 vs GPT-4o-mini 42/54; o4 Mini better decomposes goals and recovery steps in our agentic tests.
• Tool calling: GPT-4o-mini 4 vs o4 Mini 5 — o4 Mini tied for 1st, GPT-4o-mini rank 18/54; o4 Mini more accurate at function selection and arguments in our tool-calling suite.
• Classification: tie 4/4 — both tied for 1st among many models (use either for routing/categorization tasks).
• Long-context: GPT-4o-mini 4 vs o4 Mini 5 — o4 Mini ties for 1st (better retrieval accuracy at 30K+ tokens in our tests); note context windows: GPT-4o-mini 128k vs o4 Mini 200k.
• Persona consistency: GPT-4o-mini 4 vs o4 Mini 5 — o4 Mini tied for 1st; it resists injection and preserves character better in our prompts.
• Structured output: GPT-4o-mini 4 vs o4 Mini 5 — o4 Mini tied for 1st on JSON/schema compliance.
• Safety calibration: GPT-4o-mini 4 vs o4 Mini 1 — GPT-4o-mini ranks 6/55 in our safety calibration tests while o4 Mini ranks 32/55; GPT-4o-mini is much better at refusing harmful requests while permitting legitimate ones in our suite. External math/competition benchmarks (attributed to Epoch AI):
• MATH Level 5 (Epoch AI): GPT-4o-mini 52.6% vs o4 Mini 97.8% — o4 Mini shows a decisive edge for advanced math.
• AIME 2025 (Epoch AI): GPT-4o-mini 6.9% vs o4 Mini 81.7% — a similar large gap for Olympiad-style math problems. What this means in practice: for coding/technical math, strategic analysis, long-context retrieval, structured-output pipelines, and multilingual production, o4 Mini consistently outperforms in our benchmarks. GPT-4o-mini is significantly cheaper and scores higher only on safety calibration in our tests, making it a better fit where cost and conservative refusal behavior are the priority.

Per-token rates from the payload: GPT-4o-mini input $0.15/mTok and output $0.60/mTok; o4 Mini input $1.10/mTok and output $4.40/mTok. Using a 50/50 input/output split: 1M tokens (1,000 mTok) costs GPT-4o-mini $375 and o4 Mini $2,750. At 10M tokens it's $3,750 vs $27,500; at 100M tokens it's $37,500 vs $275,000. If you skew toward output-heavy workloads (80% output), costs rise proportionally (GPT-4o-mini ≈ $600 for 1M tokens, o4 Mini ≈ $4,400 for 1M tokens). The priceRatio in the payload (0.13636) means GPT-4o-mini is ~13.6% of o4 Mini's per-token cost (o4 Mini ≈ 7.33× more expensive). Teams with millions of tokens/month (SaaS embedding, heavy chatbots, high-output document generation) should care deeply about that gap; research and mission-critical reasoning teams may prefer paying the premium for o4 Mini's higher scores.

Choose o4 Mini if you need top-tier reasoning, math, long-context retrieval, structured-output reliability, multilingual parity, or best-in-class tool-calling — our tests show it wins 9 of 11 benchmarks and posts 97.8% on MATH Level 5 (Epoch AI). Choose GPT-4o-mini if your primary constraints are cost and safer refusal behavior — it wins safety calibration in our testing, has a 128k context window, and costs about 13.6% per token of o4 Mini, delivering huge savings at 1M–100M token volumes.