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Model comparison

GPT-4.1 nano vs o1

Data verified

Head-to-head evidence from 16 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

41.14/100
Margin
6.0pts
winning →
OpenAI
47.14/100
0 category wins3 category wins

Public leaderboard positions: GPT-4.1 nano #170 (Estimated); o1 #136 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GPT-4.1 nano and o1 share 16 comparable benchmark results. 3 of 8 categories are comparable. 5 results are unique to GPT-4.1 nano; 0 to o1.

Updated July 24, 2026
Shared results
16
GPT-4.1 nano only
5
o1 only
0
Comparable categories
3 / 8

Pick o1 if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.

Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 6 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

o1 is clearly ahead on the BenchAlign aggregate, 47.14 to 41.14. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

o1's sharpest advantage is in knowledge, where it averages 75.7 against 50.3. The single biggest benchmark swing on the page is GPQA, 50.3% to 75.7%.

o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 150.0x on output cost alone. o1 is the reasoning model in the pair, while GPT-4.1 nano is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GPT-4.1 nano gives you the larger context window at 1M, compared with 200K for o1.

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 GPT-4.1 nano and o1
CategoryGPT-4.1 nanoΔo1
KnowledgeGPT-4.1 nano50.3Margin 25.4o175.7
Inst. FollowingGPT-4.1 nano83.2Margin 9.0o192.2
MathGPT-4.1 nano1.0Margin 8.3o19.3

Decisive benchmark drivers

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

More
A · GPT-4.1 nanoB · o1
  1. GPQA

    Knowledge
    Source ↗
    A 50.3%B 75.7%
    Winner: o1Δ 25.4
    GPQA: GPT-4.1 nano scored 50.3%; o1 scored 75.7%. o1 wins this benchmark.
  2. IFEval

    Inst. Following
    Source ↗
    A 83.2%B 92.2%
    Winner: o1Δ 9
    IFEval: GPT-4.1 nano scored 83.2%; o1 scored 92.2%. o1 wins this benchmark.
  3. FrontierMath v2 (Tiers 1-3)

    Math
    Source ↗
    A 1.034%B 9.310%
    Winner: o1Δ 8.3
    FrontierMath v2 (Tiers 1-3): GPT-4.1 nano scored 1.034%; o1 scored 9.310%. o1 wins this benchmark.

Operational comparison

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

MetricGPT-4.1 nanoo1Comparison
Input / output priceUSD per 1M tokensGPT-4.1 nano$0.1 input / $0.4 outputo1$15 input / $60 outputGPT-4.1 nano has the lower combined listed price.
Generation speedtokens per secondGPT-4.1 nano181 tok/so198 tok/sGPT-4.1 nano has the higher measured throughput.
First-answer latencyseconds to first tokenGPT-4.1 nano0.63 so132.29 sGPT-4.1 nano reaches the first token sooner.
Context windowmaximum listed tokensGPT-4.1 nano1Mo1200KGPT-4.1 nano lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGPT-4.1 nanoo1Result
AA Agentic IndexSource 1.2%Not comparable
τ²-bench resultsSource 17.3%62.6%o1 leads
GDPval-AASource 0.0%Not comparable
GDPval-AASource 63Not comparable
Coding
BenchmarkGPT-4.1 nanoo1Result
AA Coding IndexSource 11.1%39.7%o1 leads
AA-SciCodeSource 25.9%35.8%o1 leads
Reasoning
BenchmarkGPT-4.1 nanoo1Result
AA-LCRSource 17.0%59.3%o1 leads
CritPtSource 0.0%0.3%o1 leads
Knowledgeo1 wins
BenchmarkGPT-4.1 nanoo1Result
MMLUSource 80.1%91.8%o1 leads
GPQASource 50.3%75.7%o1 leads
Artificial Analysis Intelligence IndexSource 9.6%23.4%o1 leads
AA-GPQA DiamondSource 51.2%74.7%o1 leads
AA-HLESource 3.9%7.7%o1 leads
AA-Omniscience IndexSource -56.4%-10.5%o1 leads
AA-Omniscience AccuracySource 13.3%34.7%o1 leads
AA-Omniscience Hallucination RateSource 80.4%69.3%o1 leads
Matho1 wins
BenchmarkGPT-4.1 nanoo1Result
FrontierMath v2 (Tiers 1-3)Source 1.034%9.310%o1 leads
Multimodal
BenchmarkGPT-4.1 nanoo1Result
AA-MMMU-ProSource 40.1%Not comparable
Design Arena WebsiteSource 1003Not comparable
Inst. Followingo1 wins
BenchmarkGPT-4.1 nanoo1Result
IFEvalSource 83.2%92.2%o1 leads
AA-IFBenchSource 32.0%70.3%o1 leads
Frequently Asked Questions (4)

Which is better, GPT-4.1 nano or o1?

o1 is ahead on BenchLM's BenchAlign leaderboard, 47.14 to 41.14. The biggest single separator in this matchup is GPQA, where the scores are 50.3% and 75.7%.

Which is better for knowledge tasks, GPT-4.1 nano or o1?

o1 has the edge for knowledge tasks in this comparison, averaging 75.7 versus 50.3. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.

Which is better for math, GPT-4.1 nano or o1?

o1 has the edge for math in this comparison, averaging 9.3 versus 1. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.

Which is better for instruction following, GPT-4.1 nano or o1?

o1 has the edge for instruction following in this comparison, averaging 92.2 versus 83.2. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.

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Last updated: July 24, 2026