Gemini 2.5 Pro vs o4-mini
Gemini 2.5 Pro (2025) and o4-mini (2025) are frontier reasoning models from Google DeepMind and OpenAI. Gemini 2.5 Pro ships a 1M-token context window, while o4-mini ships a not-yet-sourced context window. On MMLU PRO, Gemini 2.5 Pro leads by 3 pts. On pricing, o4-mini costs $0.5/1M input tokens versus $1.25/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
o4-mini is ~150% cheaper at $0.5/1M; pay for Gemini 2.5 Pro only for coding workflow support.
Specs
| Released | 2025-06-17 | 2025-04-16 |
| Context window | 1M | — |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Proprietary | Proprietary |
| Knowledge cutoff | 2025-01 | 2025-08 |
Pricing and availability
| Gemini 2.5 Pro | o4-mini | |
|---|---|---|
| Input price | $1.25/1M tokens | $0.5/1M tokens |
| Output price | $10/1M tokens | $2/1M tokens |
| Providers |
Capabilities
| Gemini 2.5 Pro | o4-mini | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Gemini 2.5 Pro | o4-mini |
|---|---|---|
| MMLU PRO | 86.2 | 83.2 |
| SWE-bench Verified | 63.2 | 68.1 |
| LiveCodeBench | 70.4 | 87.3 |
Deep dive
On shared benchmark coverage, MMLU PRO has Gemini 2.5 Pro at 86.2 and o4-mini at 83.2, with Gemini 2.5 Pro ahead by 3 points; SWE-bench Verified has Gemini 2.5 Pro at 63.2 and o4-mini at 68.1, with o4-mini ahead by 4.9 points; LiveCodeBench has Gemini 2.5 Pro at 70.4 and o4-mini at 87.3, with o4-mini ahead by 16.9 points. The largest visible gap is 16.9 points on LiveCodeBench, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on reasoning mode: o4-mini. Both models share vision, multimodal input, function calling, and tool use, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Gemini 2.5 Pro lists $1.25/1M input and $10/1M output tokens, while o4-mini lists $0.5/1M input and $2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts o4-mini lower by about $2.92 per million blended tokens. Availability is 3 providers versus 4, so concentration risk also matters.
Choose Gemini 2.5 Pro when coding workflow support are central to the workload. Choose o4-mini when coding workflow support, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which is cheaper, Gemini 2.5 Pro or o4-mini?
o4-mini is cheaper on tracked token pricing. Gemini 2.5 Pro costs $1.25/1M input and $10/1M output tokens. o4-mini costs $0.5/1M input and $2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemini 2.5 Pro or o4-mini open source?
Gemini 2.5 Pro is listed under Proprietary. o4-mini is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Gemini 2.5 Pro or o4-mini?
Both Gemini 2.5 Pro and o4-mini expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Gemini 2.5 Pro or o4-mini?
Both Gemini 2.5 Pro and o4-mini expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for reasoning mode, Gemini 2.5 Pro or o4-mini?
o4-mini has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Gemini 2.5 Pro and o4-mini?
Gemini 2.5 Pro is available on Google AI Studio, GCP Vertex AI, and OpenRouter. o4-mini is available on OpenAI API, OpenRouter, OpenAI Batch API, and Replicate API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.