Model comparison

GPT-4.1 nano vs GPT-5.6 Sol

Data verified July 23, 2026

Head-to-head evidence from 18 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

GPT-4.1 nano

OpenAI

42.06/100

Margin

39.9pts

winning →

GPT-5.6 Sol

OpenAI

81.96/100

0 category wins2 category wins

Public leaderboard positions: GPT-4.1 nano #161 (Estimated); GPT-5.6 Sol #3 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GPT-4.1 nano and GPT-5.6 Sol share 18 comparable benchmark results. 2 of 8 categories are comparable. 3 results are unique to GPT-4.1 nano; 28 to GPT-5.6 Sol.

Updated July 23, 2026

Shared results: 18
GPT-4.1 nano only: 3
GPT-5.6 Sol only: 28
Comparable categories: 2 / 8

Pick GPT-5.6 Sol 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 18 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-5.6 Sol is clearly ahead on the BenchAlign aggregate, 81.96 to 42.06. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

GPT-5.6 Sol's sharpest advantage is in mathematics, where it averages 87.5 against 1. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 1.034% to 89.000%.

GPT-5.6 Sol 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-5.6 Sol 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-5.6 Sol
Category	GPT-4.1 nano	Δ	GPT-5.6 Sol
Math	GPT-4.1 nano1.0	Margin→ 86.5	GPT-5.6 Sol87.5
Knowledge	GPT-4.1 nano50.3	Margin→ 44.3	GPT-5.6 Sol94.6
Agentic	GPT-4.1 nanoNot measured	MarginNo overlap	GPT-5.6 Sol92.0
Coding	GPT-4.1 nanoNot measured	MarginNo overlap	GPT-5.6 Sol64.6
Multimodal	GPT-4.1 nanoNot measured	MarginNo overlap	GPT-5.6 Sol83.0
Inst. Following	GPT-4.1 nano83.2	MarginNo overlap	GPT-5.6 SolNot measured

Decisive benchmark drivers

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

A · GPT-4.1 nanoB · GPT-5.6 Sol

FrontierMath v2 (Tiers 1-3)
Math
Source ↗
A 1.034%B 89.000%
Winner: GPT-5.6 SolΔ 88
FrontierMath v2 (Tiers 1-3): GPT-4.1 nano scored 1.034%; GPT-5.6 Sol scored 89.000%. GPT-5.6 Sol wins this benchmark.
GPQA
Knowledge
Source ↗
A 50.3%B 94.6%
Winner: GPT-5.6 SolΔ 44.3
GPQA: GPT-4.1 nano scored 50.3%; GPT-5.6 Sol scored 94.6%. GPT-5.6 Sol wins this benchmark.

Operational comparison

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

Metric	GPT-4.1 nano	GPT-5.6 Sol	Comparison
Input / output priceUSD per 1M tokens	GPT-4.1 nano$0.1 input / $0.4 output	GPT-5.6 Sol$5 input / $30 output	GPT-4.1 nano has the lower combined listed price.
Generation speedtokens per second	GPT-4.1 nano181 tok/s	GPT-5.6 SolNot available	A complete speed comparison is not available.
First-answer latencyseconds to first token	GPT-4.1 nano0.63 s	GPT-5.6 SolNot available	A complete latency comparison is not available.
Context windowmaximum listed tokens	GPT-4.1 nano1M	GPT-5.6 Sol1M	Listed context windows are equal.

Benchmark Deep Dive

Agentic

17 benchmarks

Benchmark	GPT-4.1 nano	GPT-5.6 Sol	Result
AA Agentic IndexSource	1.2%	54.0%	GPT-5.6 Sol leads
τ²-bench resultsSource	17.3%	85.1%	GPT-5.6 Sol leads
GDPval-AASource	0.0%	61.8%	GPT-5.6 Sol leads
GDPval-AASource	41	1736	GPT-5.6 Sol leads
Terminal-Bench 2.0Source	—	91.9%	Not comparable
BrowseCompSource	—	92.2%	Not comparable
OSWorld 2.0Source	—	62.6%	Not comparable
CyberGymSource	—	84.5%	Not comparable
ExploitGymSource	—	33.7%	Not comparable
ToolathlonSource	—	58%	Not comparable
AA BriefcaseSource	—	1501	Not comparable
AA ITBenchSource	—	56.2%	Not comparable
AA Tau3 BankingSource	—	33.0%	Not comparable
AA AutomationBenchSource	—	51.2%	Not comparable
AA Harvey LABSource	—	87.2%	Not comparable
terminalBenchHardSource	—	65.9%	Not comparable
aaTerminalBench21Source	—	88%	Not comparable

Coding

8 benchmarks

Benchmark	GPT-4.1 nano	GPT-5.6 Sol	Result
AA Coding IndexSource	11.1%	77.4%	GPT-5.6 Sol leads
AA-SciCodeSource	25.9%	56.1%	GPT-5.6 Sol leads
SWE-bench ProSource	—	64.6%	Not comparable
Terminal-Bench 2.0Source	—	91.9%	Not comparable
deepSweSource	—	72.7%	Not comparable
FrontierCode 1.1 ExtendedSource	—	60.6%	Not comparable
cursorBench32Source	—	67.2%	Not comparable
VulcanBench v3Source	—	87.0%	Not comparable

Reasoning

4 benchmarks

Benchmark	GPT-4.1 nano	GPT-5.6 Sol	Result
AA-LCRSource	17.0%	73.7%	GPT-5.6 Sol leads
CritPtSource	0.0%	32.3%	GPT-5.6 Sol leads
ARC-AGI-3Source	—	7.8%	Not comparable
GeneBench-ProSource	—	28.7%	Not comparable

KnowledgeGPT-5.6 Sol wins

11 benchmarks

Benchmark	GPT-4.1 nano	GPT-5.6 Sol	Result
MMLUSource	80.1%	—	Not comparable
GPQASource	50.3%	94.6%	GPT-5.6 Sol leads
Artificial Analysis Intelligence IndexSource	9.6%	58.9%	GPT-5.6 Sol leads
AA-GPQA DiamondSource	51.2%	94.1%	GPT-5.6 Sol leads
AA-HLESource	3.9%	47.2%	GPT-5.6 Sol leads
AA-Omniscience IndexSource	-56.4%	21.7%	GPT-5.6 Sol leads
AA-Omniscience AccuracySource	13.3%	58.5%	GPT-5.6 Sol leads
AA-Omniscience Hallucination RateSource	80.4%	88.8%	GPT-4.1 nano leads
GPQA-DSource	—	94.6%	Not comparable
HealthBench ProfessionalSource	—	60.5%	Not comparable
HealthBench HardSource	—	33.1%	Not comparable

MathGPT-5.6 Sol wins

3 benchmarks

Benchmark	GPT-4.1 nano	GPT-5.6 Sol	Result
FrontierMath v2 (Tiers 1-3)Source	1.034%	89.000%	GPT-5.6 Sol leads
FrontierMath (legacy)Source	—	89%	Not comparable
FrontierMath v2 (Tier 4)Source	—	83.000%	Not comparable

Multimodal

4 benchmarks

Benchmark	GPT-4.1 nano	GPT-5.6 Sol	Result
AA-MMMU-ProSource	40.1%	83.4%	GPT-5.6 Sol leads
Design Arena WebsiteSource	1003	—	Not comparable
MMMU-ProSource	—	83%	Not comparable
MMMU-Pro w/ PythonSource	—	84.6%	Not comparable

Inst. Following

2 benchmarks

Benchmark	GPT-4.1 nano	GPT-5.6 Sol	Result
IFEvalSource	83.2%	—	Not comparable
AA-IFBenchSource	32.0%	72.7%	GPT-5.6 Sol leads

Frequently Asked Questions (3)

Which is better, GPT-4.1 nano or GPT-5.6 Sol?

GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 42.06. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 1.034% and 89.000%.

Which is better for knowledge tasks, GPT-4.1 nano or GPT-5.6 Sol?

GPT-5.6 Sol has the edge for knowledge tasks in this comparison, averaging 94.6 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-5.6 Sol?

GPT-5.6 Sol has the edge for math in this comparison, averaging 87.5 versus 1. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.

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Last updated: July 23, 2026

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