Gemini 3.1 Pro Preview vs GPT-5 Mini

Across our 12-test suite (internal scoring 1–5 and external Epoch AI measures where available), Gemini 3.1 Pro Preview wins 3 tests, GPT-5 Mini wins 2, and 7 tests tie. Head-to-head highlights from our testing: - Gemini wins creative_problem_solving 5 vs 4, ranking tied for 1st (tied with 7 others) — meaning it produces more non-obvious, feasible ideas in our prompts. - Gemini wins tool_calling 4 vs 3; Gemini’s rank is 18 of 54 (many models share scores) while GPT-5 Mini ranks 47 of 54 — in practice Gemini selects and sequences functions more accurately. - Gemini wins agentic_planning 5 vs 4 and is tied for 1st (tied with 14 others), so it better decomposes goals and recovery steps in our tests. - GPT-5 Mini wins classification 4 vs 2 (GPT-5 Mini tied for 1st among 29 others), so it is stronger for routing/categorization tasks in our suite. - GPT-5 Mini also wins safety_calibration 3 vs 2 (rank 10 of 55 vs Gemini rank 12), so it more reliably refuses harmful prompts while permitting legitimate ones in our scenarios. - Multiple categories tie (structured_output, strategic_analysis, constrained_rewriting, faithfulness, long_context, persona_consistency, multilingual) at equal scores of 4–5, meaning both models perform at top levels for schema adherence, nuanced reasoning, long-context retrieval, persona maintenance, and multilingual output. External benchmarks (Epoch AI): GPT-5 Mini scores 64.7% on SWE-bench Verified, 97.8% on MATH Level 5, and 86.7% on AIME 2025 (all cited to Epoch AI). Gemini 3.1 Pro Preview scores 95.6% on AIME 2025 (Epoch AI). In short: Gemini is the better choice for agentic workflows and tool-driven tasks; GPT-5 Mini is better value and shows stronger classification and safety calibration in our tests, with strong math (MATH Level 5) and a mid-tier SWE-bench Verified placement for code tasks.

Actual per-mTok prices: Gemini 3.1 Pro Preview charges $2 input / $12 output; GPT-5 Mini charges $0.25 input / $2 output. Assuming a 50/50 split of input/output tokens, total cost per 1M tokens: Gemini ≈ $7.00 (0.5M*$2 + 0.5M*$12), GPT-5 Mini ≈ $1.125 (0.5M*$0.25 + 0.5M*$2). At scale: 10M tokens/month → Gemini ≈ $70, GPT-5 Mini ≈ $11.25; 100M tokens/month → Gemini ≈ $700, GPT-5 Mini ≈ $112.50. The cost gap grows linearly: organizations generating tens to hundreds of millions of tokens should care — GPT-5 Mini cuts token spend by ~6× in output and ~8× in input, producing large savings for high-volume chat, assistants, or analytics pipelines. Teams that depend on advanced agentic workflows, multimodal long-context reasoning, or very large outputs may justify Gemini’s premium; cost-sensitive products or experimentation benefit from GPT-5 Mini’s lower price point.

Choose Gemini 3.1 Pro Preview if you need: - Better tool-calling and agentic planning (tool_calling 4 vs 3; agentic_planning 5 vs 4) - Strong creative problem solving (5 vs 4) - Multimodal large-context workflows and willingness to pay a premium for higher-confidence agentic outputs Choose GPT-5 Mini if you need: - Much lower token cost (input $0.25/output $2 vs Gemini $2/$12) and high-volume deployment savings - Better classification and safety calibration (classification 4 vs 2; safety_calibration 3 vs 2) - Strong competitive math performance (97.8% on MATH Level 5, Epoch AI) and a balanced tradeoff of capability to price