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Model comparison

o1-pro vs o3-mini

Data verified

Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.

OpenAI
45.94/100
Margin
1.5pts
winning →
OpenAI
47.41/100
1 category wins0 category wins

Public leaderboard positions: o1-pro #141 (Estimated); o3-mini #136 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. o1-pro and o3-mini share 2 comparable benchmark results. 1 of 8 categories are comparable. 0 results are unique to o1-pro; 8 to o3-mini.

Updated July 24, 2026
Shared results
2
o1-pro only
0
o3-mini only
8
Comparable categories
1 / 8

Pick o3-mini if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority.

Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

o3-mini has the cleaner BenchAlign overall profile here, landing at 47.41 versus 45.94. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

o1-pro is also the more expensive model on tokens at $150.00 input / $600.00 output per 1M tokens, versus $1.10 input / $4.40 output per 1M tokens for o3-mini. That is roughly 136.4x on output cost alone.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for o1-pro and o3-mini
Categoryo1-proΔo3-mini
Knowledgeo1-pro79.0Margin 1.8o3-mini77.2
Codingo1-proNot measuredMarginNo overlapo3-mini49.3
Inst. Followingo1-proNot measuredMarginNo overlapo3-mini93.9

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · o1-proB · o3-mini
  1. GPQA

    Knowledge
    Source ↗
    A 79%B 77.2%
    Winner: o1-proΔ 1.8
    GPQA: o1-pro scored 79%; o3-mini scored 77.2%. o1-pro wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

Metrico1-proo3-miniComparison
Input / output priceUSD per 1M tokenso1-pro$150 input / $600 outputo3-mini$1.1 input / $4.4 outputo3-mini has the lower combined listed price.
Generation speedtokens per secondo1-proNot availableo3-mini160 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokeno1-proNot availableo3-mini7.12 sA complete latency comparison is not available.
Context windowmaximum listed tokenso1-pro200Ko3-mini200KListed context windows are equal.

Benchmark Deep Dive

Agentic
Benchmarko1-proo3-miniResult
τ²-bench resultsSource 28.7%Not comparable
Coding
Benchmarko1-proo3-miniResult
SWE-bench VerifiedSource 49.3%Not comparable
AA-SciCodeSource 39.9%Not comparable
Knowledgeo1-pro wins
Benchmarko1-proo3-miniResult
GPQASource 79%77.2%o1-pro leads
Artificial Analysis Intelligence IndexSource 18.9%19.0%o3-mini leads
MMLUSource 86.9%Not comparable
AA-GPQA DiamondSource 74.8%Not comparable
AA-HLESource 8.7%Not comparable
Math
Benchmarko1-proo3-miniResult
AIME 2024Source 87.3%Not comparable
Inst. Following
Benchmarko1-proo3-miniResult
IFEvalSource 93.9%Not comparable
Frequently Asked Questions (2)

Which is better, o1-pro or o3-mini?

o3-mini is ahead on BenchLM's BenchAlign leaderboard, 47.41 to 45.94. The biggest single separator in this matchup is GPQA, where the scores are 79% and 77.2%.

Which is better for knowledge tasks, o1-pro or o3-mini?

o1-pro has the edge for knowledge tasks in this comparison, averaging 79 versus 77.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.

Related Comparisons

Last updated: July 24, 2026

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