GPT-4o-mini vs GPT-5.4

Across our 12-test suite GPT-5.4 wins most dimensions. Summary by test (scores in our testing):

• Agentic planning: GPT-5.4 5 vs GPT-4o-mini 3 — GPT-5.4 ties for 1st (tied with 14 others), meaning it reliably decomposes goals and plans recoveries in our evaluation.
• Structured output: 5 vs 4 — GPT-5.4 ties for 1st, so it better matches JSON/schema constraints in practice.
• Tool calling: tie 4 vs 4 — both models performed similarly on function selection and argument accuracy in our tests (rank 18 of 54 for each).
• Long context: 5 vs 4 — GPT-5.4 ties for 1st (tied with 36 others); expect stronger retrieval across 30K+ token contexts. GPT-4o-mini still scores 4 — solid but not top-tier for extreme context.
• Faithfulness: 5 vs 3 — GPT-5.4 is much less prone to hallucination in our tests (ranked tied for 1st), while GPT-4o-mini ranked 52 of 55 on faithfulness.
• Strategic analysis: 5 vs 2 — GPT-5.4 excels at nuanced tradeoff reasoning with numbers; GPT-4o-mini struggled on our prompts.
• Constrained rewriting: 4 vs 3 — GPT-5.4 is better at tight character-limit compressions (rank 6 of 53).
• Creative problem solving: 4 vs 2 — GPT-5.4 produced more feasible, non‑obvious ideas in our tasks (rank 9 of 54).
• Safety calibration: 5 vs 4 — GPT-5.4 tied for 1st on refusing harmful requests while permitting valid ones; GPT-4o-mini scored well but lower (rank 6 of 55).
• Persona consistency and multilingual: GPT-5.4 both 5 vs GPT-4o-mini 4 — better at staying in character and non‑English outputs in our tests.
• Classification: GPT-4o-mini 4 vs GPT-5.4 3 — GPT-4o-mini ties for 1st (with many models) on simple routing/categorization tasks, so it’s a cost‑efficient choice for classification-heavy flows. External benchmarks (Epoch AI): GPT-5.4 scores 76.9% on SWE-bench Verified (Epoch AI), rank 2 of 12, and 95.3% on AIME 2025 (Epoch AI), rank 3 of 23. GPT-4o-mini scored 52.6% on MATH Level 5 and 6.9% on AIME 2025 (Epoch AI). These external results support GPT-5.4’s superiority on coding/math-style evaluations and advanced reasoning in our comparative view.

Raw pricing (per thousand tokens): GPT-4o-mini = $0.15 input / $0.60 output; GPT-5.4 = $2.50 input / $15.00 output. Using a simple 50/50 input-output split per million tokens: GPT-4o-mini costs $375 per 1M tokens (0.15500 + 0.60500 = $75 + $300). GPT-5.4 costs $8,750 per 1M tokens (2.50500 + 15500 = $1,250 + $7,500). Scaled to monthly volumes: 10M tokens → $3,750 (GPT-4o-mini) vs $87,500 (GPT-5.4); 100M tokens → $37,500 vs $875,000. The payload’s priceRatio (0.04) reflects that GPT-4o-mini costs roughly 4% of GPT-5.4 on a per-token basis. Who should care: startups, high-volume chat or content apps, and prototyping teams will feel this gap at 10M+ tokens; research labs or mission‑critical apps that need top long-context, faithfulness, and planning may justify GPT-5.4’s premium.

Choose GPT-4o-mini if you need low-cost, high-throughput classification, chat, or multimodal inference at scale — it’s $0.15/$0.60 per mTok and ties on tool calling while winning classification in our testing. Choose GPT-5.4 if you require top faithfulness, long-context retrieval (1,050,000 token window), agentic planning, structured-output compliance, or best-in-class reasoning — it consistently wins 10 vs 1 benchmarks in our tests, but costs roughly 25× to 40× more per mTok depending on input/output mix.