As of August 20, 2026, o3 is 11% cheaper per million tokens than Gemini 2.5 Pro. Gemini 2.5 Pro is $1.25 / $10.00 per million input/output tokens versus o3 at $2.00 / $8.00. Sources: https://ai.google.dev/gemini-api/docs/pricing and https://developers.openai.com/api/docs/pricing
Sources: Gemini API pricing (https://ai.google.dev/gemini-api/docs/pricing); OpenAI API pricing (https://developers.openai.com/api/docs/pricing)
Gemini 2.5 Pro
Input
$1.25
Output
$10.00
o3
OpenAI
Input
$2.00
Output
$8.00
Token pricing, specs, and benchmarks side by side
Gemini 2.5 Proo3Verdict
o3 offers both lower pricing and stronger benchmark performance across the board, making it the clear value leader in this comparison.
As of August 20, 2026, o3 is 11% cheaper on blended LLM API pricing. o3 costs $2.00 per million input tokens and $8.00 per million output tokens ($10.00 blended 1M-in + 1M-out). Gemini 2.5 Pro costs $1.25 / $10.00 per million tokens ($11.25 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.
Gemini 2.5 Pro Gemini API pricing is $1.25 input and $10.00 output per million tokens via Google. o3 OpenAI API pricing is $2.00 input and $8.00 output per million tokens via OpenAI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
o3 leads on SWE-bench Verified: Gemini 2.5 Pro at 63.2% vs o3 at 69.1%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
Gemini 2.5 Pro supports a 1M token context window, while o3 supports 200K 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.
o3 leads on 15 of 25 shared benchmarks versus Gemini 2.5 Pro's 10 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.
Both Gemini 2.5 Pro and o3 are production API models. For cost-sensitive production traffic, o3 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.
Yes. Call Gemini 2.5 Pro through Google and o3 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.
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.
Gemini 2.5 Pro supports up to 66K output tokens per request, while o3 supports up to 100K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Gemini 2.5 Pro runs at approximately 85 tokens/second while o3 runs at 50 tokens/second. Gemini 2.5 Pro 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.
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 o3 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
This comparison covers API pricing, context window, throughput, and benchmark scores. Gemini 2.5 Pro costs $1.25/M input and $10.00/M output. o3 costs $2.00/M input and $8.00/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
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