Which is cheaper, Gemini 2.5 Pro or o1-mini?
As of August 20, 2026, Gemini 2.5 Pro is 25% cheaper on blended LLM API pricing. Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens ($11.25 blended 1M-in + 1M-out). o1-mini costs $3.00 / $12.00 per million tokens ($15.00 blended). Sources: https://ai.google.dev/gemini-api/docs/pricing and https://developers.openai.com/api/docs/pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does Gemini 2.5 Pro vs o1-mini cost per million tokens?
Gemini 2.5 Pro Gemini API pricing is $1.25 input and $10.00 output per million tokens via Google. o1-mini OpenAI API pricing is $3.00 input and $12.00 output per million tokens via OpenAI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, Gemini 2.5 Pro or o1-mini?
Gemini 2.5 Pro has a published SWE-bench Verified score of 63.2%. o1-mini does not have that eval on this page yet.
What is the context window for Gemini 2.5 Pro vs o1-mini?
Gemini 2.5 Pro supports a 1M token context window, while o1-mini supports 128K tokens. Gemini 2.5 Pro offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Which model performs better on benchmarks, Gemini 2.5 Pro or o1-mini?
Gemini 2.5 Pro leads on 11 of 12 shared benchmarks versus o1-mini's 1 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Is Gemini 2.5 Pro or o1-mini better for production use?
Both Gemini 2.5 Pro and o1-mini are production API models. For cost-sensitive production traffic, Gemini 2.5 Pro has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Can I switch between Gemini 2.5 Pro and o1-mini in my app?
Yes. Call Gemini 2.5 Pro through Google and o1-mini through OpenAI with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
How accurate is this Gemini 2.5 Pro vs o1-mini pricing data?
List rates are the latest published Gemini API pricing and OpenAI API pricing, quoted per million tokens. Official rate sheets: https://ai.google.dev/gemini-api/docs/pricing and https://developers.openai.com/api/docs/pricing. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
What is the output token limit for Gemini 2.5 Pro and o1-mini?
Gemini 2.5 Pro supports up to 66K output tokens per request, while o1-mini supports up to 66K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Which model has better throughput, Gemini 2.5 Pro or o1-mini?
Gemini 2.5 Pro runs at approximately 85 tokens/second while o1-mini runs at 115 tokens/second. o1-mini is faster in raw throughput. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
How do I switch the models in this Gemini 2.5 Pro vs o1-mini comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Gemini 2.5 Pro or o1-mini from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
