Gemini 3 Flash Preview vs GPT-5 Mini

We ran our 12-test suite and compared model-specific ranks and external benchmarks. Wins/ties: Gemini wins creative_problem_solving (5 vs 4), tool_calling (5 vs 3), and agentic_planning (5 vs 4); GPT-5 Mini wins safety_calibration (3 vs 1). Eight tests tie at equal scores (structured_output, strategic_analysis, constrained_rewriting, faithfulness, classification, long_context, persona_consistency, multilingual). Tool calling: Gemini scores 5 and is tied for 1st (tied with 16 others out of 54), while GPT-5 Mini scores 3 and ranks 47/54 — in practice Gemini will select functions, arguments, and sequencing far more reliably for agentic tool workflows. Structured output: both score 5 and are tied for 1st (tied with 24 others of 54), so both are strong at JSON/schema compliance. Safety calibration: GPT-5 Mini scores 3 (rank 10/55) versus Gemini’s 1 (rank 32/55) — GPT-5 Mini refuses or permits requests more appropriately in our tests. Creative problem solving and agentic planning: Gemini’s 5s (ranked tied for 1st across several tests) mean better non-obvious ideas and goal decomposition for multi-step agents. Long context and persona consistency are identical (both score 5 and tie for 1st), so large-context retrieval and character maintenance are comparable. External benchmarks (Epoch AI): on SWE-bench Verified Gemini scores 75.4% vs GPT-5 Mini 64.7% (Gemini places higher on real GitHub issue resolution), while GPT-5 Mini scores 97.8% on MATH Level 5 (Epoch AI) — higher than Gemini’s missing/absent math_level_5 score in our payload — and Gemini scores 92.8% on AIME 2025 vs GPT-5 Mini 86.7% (Epoch AI). These external results reinforce that Gemini is stronger on coding/problem-resolution in SWE-bench and AIME, while GPT-5 Mini is exceptional on MATH Level 5.

Per the payload, Gemini 3 Flash Preview charges $0.50 input / $3.00 output per mTok; GPT-5 Mini charges $0.25 input / $2.00 output per mTok. Assuming a balanced 50/50 split of input/output tokens: 1M tokens = 1,000 mTok → Gemini ≈ $3,500, GPT-5 Mini ≈ $2,250 (Gemini costs $1,250 more). At 10M tokens (10,000 mTok) Gemini ≈ $35,000 vs GPT-5 Mini ≈ $22,500 (save $12,500); at 100M tokens Gemini ≈ $350,000 vs GPT-5 Mini ≈ $225,000 (save $125,000). If your usage is output-heavy (e.g., >80% output tokens), the absolute gap widens because Gemini’s $3.00 output rate is the dominant driver. Teams processing millions of tokens monthly (SaaS products, large-scale chatbots, code assistants) should care about the gap; individual developers or low-volume apps are less affected but will still see ~50% higher spend with Gemini on comparable traffic profiles.

Choose Gemini 3 Flash Preview if you need robust tool calling, agentic planning, and creative problem solving (it scores 5 on tool_calling, agentic_planning, creative_problem_solving and ranks tied for 1st on many developer-facing tests) and you can absorb ~50% higher per-token spend. Choose GPT-5 Mini if you need a lower-cost model with better safety calibration (3 vs 1), top math_level_5 performance (97.8% on Epoch AI), and solid structured-output/long-context behavior — especially for volume-sensitive deployments.