Gemini 1.5 Pro vs o3-mini
o3-mini leads the LLM Stats Score 21.6 to 12.2. o3-mini is 2.3x cheaper per token.
Google · OpenAI · Updated for 2026
Which is better?
o3-mini leads the overall LLM Stats Score 21.6 to 12.2, ranking #173 overall.
In the 4 individual benchmarks reported for both models, o3-mini wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, o3-mini is roughly 2.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 1.5 Pro also accepts a larger context window (2,097,152 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemini 1.5 Pro
- you process long inputs — it offers a 2,097,152 token context window
Choose o3-mini
- overall performance matters — it scores 21.6 and ranks #173 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- cost matters — it's about 2.3x cheaper per token
- you want the most recent training data — it shipped Jan 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
23 reported for Gemini 1.5 Pro · 25 for o3-mini
Gemini 1.5 Pro outperforms in 0 benchmarks, while o3-mini is better at 4 benchmarks (GPQA, MATH, MGSM, MMLU).
o3-mini significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 1.5 Pro ($2.50/1M tokens) is 2.3x more expensive than o3-mini ($1.10/1M tokens).
For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 2.3x more expensive than o3-mini ($4.40/1M tokens).
In conclusion, Gemini 1.5 Pro is more expensive than o3-mini.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 1.5 Pro accepts 2,097,152 input tokens compared to o3-mini's 200,000 tokens. o3-mini can generate longer responses up to 100,000 tokens, while Gemini 1.5 Pro is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Gemini 1.5 Pro supports multimodal inputs, whereas o3-mini does not.
Gemini 1.5 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 1.5 Pro
o3-mini
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
Gemini 1.5 Pro was released on 2024-05-01, while o3-mini was released on 2025-01-30.
o3-mini is 9 months newer than Gemini 1.5 Pro.
May 1, 2024
2.3 years ago
Jan 30, 2025
1.6 years ago
9mo newerKnowledge Cutoff
When training data ends
Gemini 1.5 Pro has a knowledge cutoff of 2023-11-01, while o3-mini has a cutoff of 2023-09-30.
Gemini 1.5 Pro has more recent training data (up to 2023-11-01), making it potentially better informed about events through that date compared to o3-mini (2023-09-30).
Nov 2023
2 mo newerSep 2023
Provider Availability
Gemini 1.5 Pro is available from Google. o3-mini is available from Azure, OpenAI.
Gemini 1.5 Pro
o3-mini
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 1.5 Pro and o3-mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.5 Pro vs o3-mini.