GPT-4.1 Mini vs GPT-4o-mini

Summary of head-to-head results in our 12-test suite (scores from payload). GPT-4.1 Mini wins 8 categories, GPT-4o-mini wins 2, and 2 tie. Detailed walk-through: - Long context: GPT-4.1 Mini scores 5 vs GPT-4o-mini 4. In our tests GPT-4.1 Mini is tied for 1st of 55 models for long context (tied with 36 others), so it excels at retrieval and accuracy over 30K+ tokens; GPT-4o-mini ranks 38/55. - Math (MATH Level 5, Epoch AI): GPT-4.1 Mini 87.3% vs GPT-4o-mini 52.6% (Epoch AI). This large gap implies GPT-4.1 Mini is substantially better for competition‑style math and complex symbolic work. - AIME 2025 (Epoch AI): GPT-4.1 Mini 44.7% vs GPT-4o-mini 6.9% (Epoch AI), reinforcing GPT-4.1 Mini’s advantage on hard math problems. - Multilingual: GPT-4.1 Mini scores 5 vs GPT-4o-mini 4; GPT-4.1 Mini is tied for 1st of 55 (34 others share score), so it produces stronger non‑English outputs in our testing. - Persona consistency: 5 vs 4, with GPT-4.1 Mini tied for 1st (36 others) — better at maintaining character and resisting injection. - Strategic analysis & creative problem solving: GPT-4.1 Mini (4 / 3) — better at nuanced tradeoffs and feasible idea generation (ranks 27/54 for strategic analysis). - Constrained rewriting: GPT-4.1 Mini 4 vs GPT-4o-mini 3 (GPT-4.1 Mini ranks 6/53), so it compresses content into tight limits more reliably. - Faithfulness: GPT-4.1 Mini 4 vs GPT-4o-mini 3; GPT-4.1 Mini ranks 34/55 vs GPT-4o-mini 52/55, meaning it sticks to source material better in our tests. - Agentic planning: 4 vs 3 (GPT-4.1 Mini ranks 16/54) — better goal decomposition and failure recovery. - Tool calling: tie at 4 — both models performed similarly on function selection and argument accuracy; both are ranked 18/54 in our dataset. - Structured output: tie at 4 — both match JSON/schema needs equally in our testing (rank 26/54). - Classification: GPT-4o-mini wins 4 vs 3; GPT-4o-mini is tied for 1st of 53 (29 others) on classification, so it is preferable for routing, tagging, and categorization tasks. - Safety calibration: GPT-4o-mini 4 vs GPT-4.1 Mini 2; GPT-4o-mini ranks 6/55 on safety calibration (tied with 3 others), while GPT-4.1 Mini ranks 12/55 — GPT-4o-mini is significantly better at refusing harmful requests while permitting legitimate ones in our tests. Practical implications: GPT-4.1 Mini is the pick for math, long documents, multilingual outputs, structured compression, and agentic workflows. GPT-4o-mini is the pick for safety-sensitive production, classification pipelines, and lower-cost at scale. The external Epoch AI results (MATH Level 5 and AIME 2025) back the math advantage for GPT-4.1 Mini.

Prices in the payload are per mTok; we treat mTok as 1,000 tokens for these examples. GPT-4.1 Mini charges $0.40 (input) + $1.60 (output) = $2.00 per 1k tokens. GPT-4o-mini charges $0.15 + $0.60 = $0.75 per 1k tokens. At 1,000,000 tokens/month (1,000 × 1k): GPT-4.1 Mini ≈ $2,000/month vs GPT-4o-mini ≈ $750/month. At 10M tokens: $20,000 vs $7,500. At 100M tokens: $200,000 vs $75,000. The 2.6667× price ratio (payload priceRatio) means cost-sensitive producers, high-volume APIs, and startups should prefer GPT-4o-mini to reduce infrastructure spend; teams that need superior long-context recall, math, multilingual fidelity, or agentic planning may justify GPT-4.1 Mini’s higher cost.

Choose GPT-4.1 Mini if you need: - Strong long-context retrieval and processing (1M+ token context), superior math performance (MATH Level 5 87.3% vs 52.6% by Epoch AI), better multilingual output, and higher faithfulness for research, analytics, tutoring, or complex agentic workflows — accept ~2.67× higher cost. Choose GPT-4o-mini if you need: - A lower-cost production model for classification and safety-sensitive chat or routing (safety calibration 4 vs 2, classification tied for 1st), or you operate at high token volumes where cost per 1k ($0.75 vs $2.00) materially lowers monthly spend.