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Model comparison

GPT-4.1 nano vs GPT-5.5

Data verified

Head-to-head evidence from 19 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

42.06/100
Margin
31.5pts
winning →
GPT-5.5
OpenAI
73.51/100
0 category wins2 category wins

Public leaderboard positions: GPT-4.1 nano #161 (Estimated); GPT-5.5 #9 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GPT-4.1 nano and GPT-5.5 share 19 comparable benchmark results. 2 of 8 categories are comparable. 2 results are unique to GPT-4.1 nano; 38 to GPT-5.5.

Updated July 22, 2026
Shared results
19
GPT-4.1 nano only
2
GPT-5.5 only
38
Comparable categories
2 / 8

Pick GPT-5.5 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 would rather avoid the extra latency and token burn of a reasoning model.

Confidence note. This is a partial-evidence comparison with 19 shared benchmark results across 7 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

GPT-5.5 is clearly ahead on the BenchAlign aggregate, 73.51 to 42.06. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

GPT-5.5's sharpest advantage is in mathematics, where it averages 47.6 against 1. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 1.034% to 51.700%.

GPT-5.5 is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 75.0x on output cost alone. GPT-5.5 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.

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 GPT-5.5
CategoryGPT-4.1 nanoΔGPT-5.5
MathGPT-4.1 nano1.0Margin→ 46.6GPT-5.547.6
KnowledgeGPT-4.1 nano50.3Margin→ 7.5GPT-5.557.8
AgenticGPT-4.1 nanoNot measuredMarginNo overlapGPT-5.581.6
CodingGPT-4.1 nanoNot measuredMarginNo overlapGPT-5.558.6
ReasoningGPT-4.1 nanoNot measuredMarginNo overlapGPT-5.585.0
MultimodalGPT-4.1 nanoNot measuredMarginNo overlapGPT-5.570.4
Inst. FollowingGPT-4.1 nano83.2MarginNo overlapGPT-5.5Not measured

Decisive benchmark drivers

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

More
A · GPT-4.1 nanoB · GPT-5.5

  1. FrontierMath v2 (Tiers 1-3)

    Math
    Source ↗
    A 1.034%B 51.700%
    Winner: GPT-5.5Δ 50.7
    FrontierMath v2 (Tiers 1-3): GPT-4.1 nano scored 1.034%; GPT-5.5 scored 51.700%. GPT-5.5 wins this benchmark.

  2. GPQA

    Knowledge
    Source ↗
    A 50.3%B 93.6%
    Winner: GPT-5.5Δ 43.3
    GPQA: GPT-4.1 nano scored 50.3%; GPT-5.5 scored 93.6%. GPT-5.5 wins this benchmark.

Operational comparison

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

MetricGPT-4.1 nanoGPT-5.5Comparison
Input / output priceUSD per 1M tokensGPT-4.1 nano$0.1 input / $0.4 outputGPT-5.5$5 input / $30 outputGPT-4.1 nano has the lower combined listed price.
Generation speedtokens per secondGPT-4.1 nano181 tok/sGPT-5.5Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGPT-4.1 nano0.63 sGPT-5.5Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensGPT-4.1 nano1MGPT-5.51MListed context windows are equal.

Benchmark Deep Dive

Agentic
BenchmarkGPT-4.1 nanoGPT-5.5Result
AA Agentic IndexSource 1.2%44.9%GPT-5.5 leads
τ²-bench resultsSource 17.3%93.9%GPT-5.5 leads
GDPval-AASource 0.0%49.5%GPT-5.5 leads
GDPval-AASource 411490GPT-5.5 leads
Terminal-Bench 2.0Source —82%Not comparable
CyberGymSource —81.8%Not comparable
BrowseCompSource —84.4%Not comparable
OSWorld-VerifiedSource —78.7%Not comparable
MCP AtlasSource —75.3%Not comparable
ToolathlonSource —55.6%Not comparable
APEX-Agents-AASource —37.7%Not comparable
Gert LabsSource —72.93%Not comparable
ResearchClawBenchSource —17.0%Not comparable
OSWorld 2.0Source —13.0%Not comparable
JobBenchSource —42.7%Not comparable
ExploitGymSource —13.4%Not comparable
AA BriefcaseSource —1154Not comparable
AA AutomationBenchSource —42.1%Not comparable
AA EnterpriseOps-GymSource —46.6%Not comparable
AA Harvey LABSource —86.3%Not comparable
AA ITBenchSource —45.8%Not comparable
AA Tau3 BankingSource —31.3%Not comparable
terminalBenchHardSource —60.6%Not comparable
aaTerminalBench21Source —84.3%Not comparable
Coding
BenchmarkGPT-4.1 nanoGPT-5.5Result
AA Coding IndexSource 11.1%74.9%GPT-5.5 leads
AA-SciCodeSource 25.9%56.1%GPT-5.5 leads
SWE-bench ProSource —58.6%Not comparable
Terminal-Bench 2.0Source —82.0%Not comparable
Vibe Code BenchSource —69.85%Not comparable
React Native EvalsSource —84.7%Not comparable
cursorBench31Source —59.2%Not comparable
cursorBench32Source —58.4%Not comparable
FrontierCode 1.1 MainSource —43.0%Not comparable
Reasoning
BenchmarkGPT-4.1 nanoGPT-5.5Result
AA-LCRSource 17.0%74.3%GPT-5.5 leads
CritPtSource 0.0%27.1%GPT-5.5 leads
MRCR v2 64K-128KSource —83.1%Not comparable
MRCR v2 128K-256KSource —87.5%Not comparable
ARC-AGI-2Source —85%Not comparable
KnowledgeGPT-5.5 wins
BenchmarkGPT-4.1 nanoGPT-5.5Result
MMLUSource 80.1%—Not comparable
GPQASource 50.3%93.6%GPT-5.5 leads
Artificial Analysis Intelligence IndexSource 9.6%54.8%GPT-5.5 leads
AA-GPQA DiamondSource 51.2%93.5%GPT-5.5 leads
AA-HLESource 3.9%44.3%GPT-5.5 leads
AA-Omniscience IndexSource -56.4%20.1%GPT-5.5 leads
AA-Omniscience AccuracySource 13.3%56.9%GPT-5.5 leads
AA-Omniscience Hallucination RateSource 80.4%85.5%GPT-4.1 nano leads
GPQA-DSource —93.6%Not comparable
HLESource —52.2%Not comparable
HLE w/o toolsSource —41.4%Not comparable
MathGPT-5.5 wins
BenchmarkGPT-4.1 nanoGPT-5.5Result
FrontierMath v2 (Tiers 1-3)Source 1.034%51.700%GPT-5.5 leads
FrontierMath (legacy)Source —51.7%Not comparable
FrontierMath v2 (Tier 4)Source —35.400%Not comparable
Multimodal
BenchmarkGPT-4.1 nanoGPT-5.5Result
AA-MMMU-ProSource 40.1%79.9%GPT-5.5 leads
Design Arena WebsiteSource 10031282GPT-5.5 leads
MMMU-ProSource —81.2%Not comparable
MMMU-Pro w/ PythonSource —83.2%Not comparable
OfficeQA ProSource —54.1%Not comparable
Inst. Following
BenchmarkGPT-4.1 nanoGPT-5.5Result
IFEvalSource 83.2%—Not comparable
AA-IFBenchSource 32.0%75.9%GPT-5.5 leads
Frequently Asked Questions (3)

Which is better, GPT-4.1 nano or GPT-5.5?

GPT-5.5 is ahead on BenchLM's BenchAlign leaderboard, 73.51 to 42.06. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 1.034% and 51.700%.

Which is better for knowledge tasks, GPT-4.1 nano or GPT-5.5?

GPT-5.5 has the edge for knowledge tasks in this comparison, averaging 57.8 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 GPT-5.5?

GPT-5.5 has the edge for math in this comparison, averaging 47.6 versus 1. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.

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