Gemini 2.5 Pro vs o4 Mini
For most production API use (cost-sensitive, high-throughput apps), o4 Mini is the practical winner because it matches Gemini on the majority of our benchmarks while costing much less per output token. Gemini 2.5 Pro is the better pick when you need stronger creative problem solving, a vastly larger 1,048,576-token context window, or broader modality support and are willing to pay the premium.
Gemini 2.5 Pro
Benchmark Scores
External Benchmarks
Pricing
Input
$1.25/MTok
Output
$10.00/MTok
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o4 Mini
Benchmark Scores
External Benchmarks
Pricing
Input
$1.10/MTok
Output
$4.40/MTok
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Benchmark Analysis
Across our 12-test suite the two models tie on most dimensions (structured_output, constrained_rewriting, tool_calling, faithfulness, classification, long_context, safety_calibration, persona_consistency, agentic_planning, multilingual). Specific wins: Gemini 2.5 Pro wins creative_problem_solving 5 vs 4 (our test: non-obvious, specific, feasible ideas), where Gemini ranks tied for 1st among tested models on creative_problem_solving. o4 Mini wins strategic_analysis 5 vs 4 (our test: nuanced tradeoff reasoning with real numbers) and is tied for 1st in strategic_analysis in our rankings. Both score 5/5 on long_context (Gemini and o4 Mini tied for 1st — Gemini’s context window is 1,048,576 vs o4 Mini’s 200,000) and 5/5 on tool_calling (tied for 1st), so both are strong for agentic workflows and function/argument correctness in our tests. Safety_calibration is low for both (1/5 tied), so neither model stands out on refusal/permissiveness in our suite. On external benchmarks: according to Epoch AI, o4 Mini scores 97.8% on MATH Level 5 (ranked 2 of 14 on that external math benchmark), while Gemini scores 57.6% on SWE-bench Verified (Epoch AI) and 84.2% on AIME 2025 (Epoch AI) versus o4 Mini’s 81.7% on AIME 2025. Those external results indicate o4 Mini is exceptionally strong on competitive math (MATH Level 5) per Epoch AI, while Gemini shows solid AIME performance but a lower SWE-bench Verified score. In short: for math-competition tasks give extra weight to o4 Mini (97.8% on MATH Level 5, Epoch AI); for creative ideation and very long multimodal context, Gemini has the edge in our internal suite.
Pricing Analysis
Prices in the payload are per M-token: Gemini 2.5 Pro input $1.25 + output $10.00; o4 Mini input $1.10 + output $4.40. Assuming equal input and output volume (1M input + 1M output): Gemini = $11.25/month, o4 Mini = $5.50/month. Scale: at 10M in+out tokens Gemini = $112.50 vs o4 Mini = $55.00; at 100M Gemini = $1,125 vs o4 Mini = $550. The price ratio is ~2.27x (Gemini:o4 Mini) on token billing. High-volume deployments (10M–100M tokens/month), real-time chat stacks, and cost-sensitive consumer apps should favor o4 Mini for lower run costs. Projects that need Gemini’s larger 1,048,576-token context window, extra modalities (audio/video->text), or higher creative_problem_solving score may justify the higher spend.
Real-World Cost Comparison
Bottom Line
Choose Gemini 2.5 Pro if you need: - Best creative_problem_solving in our tests (5/5) - Massive 1,048,576-token context windows for long documents - Broader modalities (text+image+file+audio+video->text) and are willing to pay ~2.27x the per-token output price. Choose o4 Mini if you need: - Cost-efficient production at scale (output $4.40 vs $10.00 per M-token) - Top strategic analysis (5/5 in our tests) and outstanding competitive-math performance (97.8% on MATH Level 5, Epoch AI) - A balanced model that ties Gemini on most other benchmarks and is better for high-volume deployments.
How We Test
We test every model against our 12-benchmark suite covering tool calling, agentic planning, creative problem solving, safety calibration, and more. Each test is scored 1–5 by an LLM judge. Read our full methodology.