GPT-4o vs o3-mini
o3-mini leads the LLM Stats Score 21.5 to 14.3. o3-mini is 2.3x cheaper per token.
OpenAI · OpenAI · Updated for 2026
Which is better?
o3-mini leads the overall LLM Stats Score 21.5 to 14.3, ranking #178 overall.
In the 20 individual benchmarks reported for both models, o3-mini wins 12; 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.
o3-mini also accepts a larger context window (200,000 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 GPT-4o
- you want predictable pricing at $2.50/M input and $10.00/M output
Choose o3-mini
- overall performance matters — it scores 21.5 and ranks #178 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 12 of 20 exact shared results
- cost matters — it's about 2.3x cheaper per token
- you process long inputs — it offers a 200,000 token context window
- 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
38 reported for GPT-4o · 25 for o3-mini
GPT-4o outperforms in 8 benchmarks (ComplexFuncBench, Multi-Challenge, OpenAI-MRCR: 2 needle 128k, SimpleQA, SWE-Lancer, SWE-Lancer (IC-Diamond subset), TAU-bench Airline, TAU-bench Retail), while o3-mini is better at 12 benchmarks (Aider-Polyglot, Aider-Polyglot Edit, AIME 2024, COLLIE, GPQA, Graphwalks BFS <128k, Graphwalks parents <128k, IFEval, Internal API instruction following (hard), MMLU, Multi-IF, SWE-Bench Verified).
o3-mini has a slight edge in benchmark performance.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-4o ($2.50/1M tokens) is 2.3x more expensive than o3-mini ($1.10/1M tokens).
For output processing, GPT-4o ($10.00/1M tokens) is 2.3x more expensive than o3-mini ($4.40/1M tokens).
In conclusion, GPT-4o is more expensive than o3-mini.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
o3-mini accepts 200,000 input tokens compared to GPT-4o's 128,000 tokens. o3-mini can generate longer responses up to 100,000 tokens, while GPT-4o is limited to 16,384 tokens.
Input capabilities
Documented input modalities across available providers
GPT-4o supports multimodal inputs, whereas o3-mini does not.
GPT-4o can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-4o
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
GPT-4o was released on 2024-08-06, while o3-mini was released on 2025-01-30.
o3-mini is 6 months newer than GPT-4o.
Aug 6, 2024
2.1 years ago
Jan 30, 2025
1.6 years ago
5mo newerKnowledge Cutoff
When training data ends
o3-mini has a documented knowledge cutoff of 2023-09-30, while GPT-4o's cutoff date is not specified.
We can confirm o3-mini's training data extends to 2023-09-30, but cannot make a direct comparison without GPT-4o's cutoff date.
—
Sep 2023
Provider Availability
GPT-4o is available from Azure, OpenAI. o3-mini is available from Azure, OpenAI.
GPT-4o
o3-mini
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4o and o3-mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4o vs o3-mini.