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OpenAI o1-mini OpenAI

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9/23/24, 2:49 AM
OpenAI o1-mini | OpenAI
September 12, 2024
OpenAI o1-mini
Advancing cost-efficient reasoning.
Contributions
We're releasing OpenAI o1-mini, a cost-efficient reasoning model. o1-mini excels at
STEM, especially math and coding—nearly matching the performance of OpenAI o1
on evaluation benchmarks such as AIME and Codeforces. We expect o1-mini will be a
faster, cost-effective model for applications that require reasoning without broad
world knowledge.
Today, we are launching o1-mini to tier 5 API users at a cost that is 80% cheaper than
OpenAI o1-preview. ChatGPT Plus, Team, Enterprise, and Edu users can use o1-mini
as an alternative to o1-preview, with higher rate limits and lower latency (see Model
Speed).
Optimized for STEM Reasoning
Large language models such as o1 are pre-trained on vast text datasets. While these
high-capacity models have broad world knowledge, they can be expensive and slow
for real-world applications. In contrast, o1-mini is a smaller model optimized for STEM
reasoning during pretraining. After training with the same high-compute
reinforcement learning (RL) pipeline as o1, o1-mini achieves comparable performance
on many useful reasoning tasks, while being significantly more cost efficient.
https://openai.com/index/openai-o1-mini-advancing-cost-efficient-reasoning/
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OpenAI o1-mini | OpenAI
When evaluated on benchmarks requiring intelligence and reasoning, o1-mini
performs well compared to o1-preview and o1. However, o1-mini performs worse on
tasks requiring non-STEM factual knowledge (see Limitations).
Read aloud
Math Performance vs Inference Cost
GPT-4o
GPT-4o mini
o1-preview
o1-mini
o1
80%
AIME
60%
40%
20%
0%
0
10
20
30
40
50
60
70
80
90
100
Inference Cost (%)
Mathematics: In the high school AIME math competition, o1-mini (70.0%) is
competitive with o1 (74.4%)–while being significantly cheaper–and outperforms o1preview (44.6%). o1-mini’s score (about 11/15 questions) places it in approximately the
top 500 US high-school students.
Coding: On the Codeforces competition website, o1-mini achieves 1650 Elo, which is
again competitive with o1 (1673) and higher than o1-preview (1258). This Elo score
puts the model at approximately the 86th percentile of programmers who compete
on the Codeforces platform. o1-mini also performs well on the HumanEval coding
benchmark and high-school level cybersecurity capture the flag challenges (CTFs).
Codeforces
https://openai.com/index/openai-o1-mini-advancing-cost-efficient-reasoning/
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OpenAI o1-mini | OpenAI
1650
o1-mini
1258
o1-preview
900
GPT-4o
0
200
400
600
800
1,000
1,200
1,400
1,600
1
Elo


HumanEval
o1-mini
92.4%
o1-preview
92.4%
90.2%
GPT-4o
0
10
20
30
40
50
60
70
80
90
Accuracy


Cybersecurity CTFs
28.7%
o1-mini
43
o1-preview
20.0%
GPT-4o
0
GPT-4o 20.0%
5
10
15
20
25
30
35
40
Accuracy (Pass@12)


STEM: On some academic benchmarks requiring reasoning, such as GPQA (science)
and MATH-500, o1-mini outperforms GPT-4o. o1-mini does not perform as well as
GPT-4o on tasks such as MMLU and lags behind o1-preview on GPQA due to its lack
of broad world knowledge.
MMLU
0-shot CoT
https://openai.com/index/openai-o1-mini-advancing-cost-efficient-reasoning/
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OpenAI o1-mini | OpenAI
88.7%
GPT-4o
85.2%
o1-mini
90.8%
o1-preview
92.3%
o1
0
10
20
30
40
50
60
70
80
90


GPQA
Diamond, 0-shot CoT
53.6%
GPT-4o
60.0%
o1-mini
73.3%
o1-preview
o1
77.3%
o1-preview 73.3%
0
10
20
30
40
50
60
70
80
90


MATH-500
0-shot CoT
60.3%
GPT-4o
90.0%
o1-mini
85.5%
o1-preview
o1
94.
o1-preview 85.5%
0
10
20
30

40
50
60
70
80
90

Human preference evaluation: We had human raters compare o1-mini to GPT-4o on
challenging, open-ended prompts in various domains, using the same methodology
as our o1-preview vs GPT-4o comparison. Similar to o1-preview, o1-mini is preferred to
GPT-4o in reasoning-heavy domains, but is not preferred to GPT-4o in languagefocused domains.
Human preference evaluation vs chatgpt-4o-latest
o1-preview
o1-mini
https://openai.com/index/openai-o1-mini-advancing-cost-efficient-reasoning/
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OpenAI o1-mini | OpenAI
100
Win Rate vs GPT-4o (%)
80
60
40
20
0
Personal Writing
Editing Text
Computer Programming
Data Analysis
Mathematical Calcula
Domain


Model Speed
As a concrete example, we compared responses from GPT-4o, o1-mini, and o1preview on a word reasoning question. While GPT-4o did not answer correctly, both
o1-mini and o1-preview did, and o1-mini reached the answer around 3-5x faster.
https://openai.com/index/openai-o1-mini-advancing-cost-efficient-reasoning/
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OpenAI o1-mini | OpenAI
Chat speed comparison
Safety
o1-mini is trained using the same alignment and safety techniques as o1-preview. The
model has 59% higher jailbreak robustness on an internal version of the
StrongREJECT dataset compared to GPT-4o. Before deployment, we carefully
assessed the safety risks of o1-mini using the same approach to preparedness,
external red-teaming, and safety evaluations as o1-preview. We are publishing the
detailed results from these evaluations in the accompanying system card.
Metric
GPT-4o
o1-mini
% Safe completions
refusal on harmful
0.99
0.99
% Safe completions on
harmful prompts
(Challenging: jailbreaks &
edge cases)
0.714
0.932
% Compliance on benign
edge cases (“not overrefusal”)
0.91
0.923
[email protected]
0.22
0.83
0.77
0.95
prompts (standard)
StrongREJECT jailbreak
eval (Souly et al. 2024)
Human sourced jailbreak
eval
https://openai.com/index/openai-o1-mini-advancing-cost-efficient-reasoning/
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Limitations and What’s Next
Due to its specialization on STEM reasoning capabilities, o1-mini’s factual knowledge
on non-STEM topics such as dates, biographies, and trivia is comparable to small
LLMs such as GPT-4o mini. We will improve these limitations in future versions, as
well as experiment with extending the model to other modalities and specialities
outside of STEM.
Authors
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GPT-4
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