Gemini 2.5 Pro vs GPT-4.1 Nano

Summary of our 12-test comparison (scores are from our testing):

• Gemini 2.5 Pro wins: strategic_analysis 4 vs 2 (Gemini ranks 27 of 54), creative_problem_solving 5 vs 2 (Gemini tied for 1st), tool_calling 5 vs 4 (Gemini tied for 1st; GPT rank 18), classification 4 vs 3 (Gemini tied for 1st; GPT rank 31), long_context 5 vs 4 (Gemini tied for 1st with 36 others; GPT rank 38), persona_consistency 5 vs 4 (Gemini tied for 1st), multilingual 5 vs 4 (Gemini tied for 1st).
• GPT‑4.1 Nano wins: constrained_rewriting 4 vs 3 (GPT rank 6 of 53 vs Gemini rank 31), safety_calibration 2 vs 1 (GPT rank 12 vs Gemini rank 32). These wins mean GPT‑4.1 Nano is better at tight, compressed rewriting tasks and refuses/permits balance in our safety tests.
• Ties: structured_output 5/5 (both tied for 1st), faithfulness 5/5 (both tied for 1st), agentic_planning 4/4 (both rank 16). For practical tasks this means both models produce compliant JSON/structured outputs and both are faithful to source material in our tests.
• External benchmarks (Epoch AI): Gemini scores 57.6% on SWE-bench Verified and 84.2% on AIME 2025 (Epoch AI); GPT‑4.1 Nano scores 70% on MATH Level 5 and 28.9% on AIME 2025 (Epoch AI). Use these third-party measures as supplementary evidence: Gemini’s high AIME score indicates stronger olympiad-style math performance in our dataset, while GPT‑4.1 Nano’s MATH Level 5 result (70%) shows solid performance on competition math per Epoch AI. What this means for real tasks: choose Gemini when you need reliable multi-hundred-thousand-token retrieval, complex tool orchestration, multilingual fidelity, or open-ended creative problem solving. Choose GPT‑4.1 Nano when you need a low-latency, low-cost model that handles constrained rewriting and has stronger safety calibration in our tests.

Costs are per mTok (1,000 tokens). Gemini 2.5 Pro: input $1.25/mTok, output $10.00/mTok. GPT‑4.1 Nano: input $0.10/mTok, output $0.40/mTok. Assuming a 50/50 input/output split: for 1M tokens (1,000 mTok total → 500 mTok input + 500 mTok output) Gemini costs $625 + $5,000 = $5,625/month; GPT‑4.1 Nano costs $50 + $200 = $250/month. At 10M tokens/month multiply those totals by 10 (Gemini $56,250 vs Nano $2,500). At 100M tokens/month multiply by 100 (Gemini $562,500 vs Nano $25,000). The 25x priceRatio in the payload means high-volume apps (SaaS, consumer chat, large-scale embeddings/analysis) should prefer GPT‑4.1 Nano for cost-sensitive inference; teams that need the top-tier long-context, tool orchestration, and creative/problem-solving accuracy should budget for Gemini 2.5 Pro.

Choose Gemini 2.5 Pro if you need: long-context retrieval (30K+ token workflows), robust tool calling and orchestration, highest scores on creative problem solving and multilingual/persona tasks, or superior AIME 2025 performance (84.2% on Epoch AI). Budget for $1.25/mTok input and $10.00/mTok output. Choose GPT‑4.1 Nano if you need: the lowest inference cost (input $0.10/mTok, output $0.40/mTok), tight constrained rewriting, or better safety calibration in our tests — ideal for high-volume consumer apps or latency-sensitive endpoints.