Gemini 3 Flash Preview vs GPT-4.1 Nano

Summary of our 12-test head-to-head (all internal 1–5 scores noted as "in our testing"): Wins (Gemini): strategic_analysis 5 vs 2 (Gemini tied for 1st of 54 on strategic analysis), creative_problem_solving 5 vs 2 (Gemini tied for 1st), tool_calling 5 vs 4 (Gemini tied for 1st of 54; GPT ranks 18 of 54), classification 4 vs 3 (Gemini tied for 1st of 53; GPT ranks 31 of 53), long_context 5 vs 4 (Gemini tied for 1st of 55; GPT ranks 38 of 55), persona_consistency 5 vs 4 (Gemini tied for 1st of 53; GPT rank 38), agentic_planning 5 vs 4 (Gemini tied for 1st; GPT rank 16), multilingual 5 vs 4 (Gemini tied for 1st; GPT rank 36). Ties: structured_output 5 vs 5 (both tied for 1st with 24 others — strong JSON/schema handling), constrained_rewriting 4 vs 4 (both rank 6 of 53), faithfulness 5 vs 5 (both tied for 1st). GPT-4.1 Nano wins safety_calibration 2 vs 1 (GPT rank 12 of 55 vs Gemini rank 32 of 55), indicating GPT refuses or permits requests more appropriately in our safety checks. External benchmarks (Epoch AI): Gemini scores 75.4 on SWE-bench Verified (Epoch AI), ranking 3 of 12 — supporting its coding/tool strengths; Gemini scores 92.8 on AIME 2025 (Epoch AI), ranking 5 of 23, showing strong olympiad-style math performance in that data. GPT-4.1 Nano posts 70 on MATH Level 5 (Epoch AI) and 28.9 on AIME 2025 (Epoch AI) in the payload; its moderate math/exam scores match its weaker strategic and creative test results in our suite. Practical meaning: choose Gemini when you need best-in-class tool selection, multi-step planning, and retrieval over massive contexts (30K+ tokens). Choose GPT-4.1 Nano when cost, latency, and slightly stronger safety refusals are priorities; it matches Gemini on structured output and faithfulness but loses on most analytic and agentic metrics.

Per-1k (mTok) pricing from the payload: Gemini 3 Flash Preview charges $0.50 input + $3.00 output = $3.50 per 1k tokens; GPT-4.1 Nano charges $0.10 input + $0.40 output = $0.50 per 1k tokens. That translates to: - For 1M input tokens: Gemini $500, GPT $100. For 1M output tokens: Gemini $3,000, GPT $400. If you assume 1M input + 1M output (common for chat-style workloads), Gemini costs $3,500 vs GPT $500. Scale effects: at 10M (1:1 in/out) Gemini ≈ $35,000 vs GPT ≈ $5,000; at 100M Gemini ≈ $350,000 vs GPT ≈ $50,000. High-volume apps (>=10M tokens/mo) should care strongly—GPT-4.1 Nano lowers TCO by an order of magnitude; teams prioritizing top-tier tool use, long-context reasoning, and math may justify Gemini's higher spend.

Choose Gemini 3 Flash Preview if you need agentic workflows, multi-step tool calling, large-context retrieval (30K+ tokens), or top math/coding performance and can afford $3.50 per 1k tokens. Choose GPT-4.1 Nano if you need a low-cost, low-latency model that preserves structured output and faithfulness while improving safety calibration; it costs $0.50 per 1k and is the pragmatic choice for high-volume or cost-sensitive production.