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Model comparison

GPT-5.4 nano vs GPT-5.6 Sol

Data verified

Head-to-head evidence from 23 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

66.79/100
Margin
15.2pts
winning →
81.96/100
0 category wins4 category wins

Public leaderboard positions: GPT-5.4 nano #25 (Supported); GPT-5.6 Sol #3 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GPT-5.4 nano and GPT-5.6 Sol share 23 comparable benchmark results. 4 of 8 categories are comparable. 6 results are unique to GPT-5.4 nano; 23 to GPT-5.6 Sol.

Updated July 23, 2026
Shared results
23
GPT-5.4 nano only
6
GPT-5.6 Sol only
23
Comparable categories
4 / 8

Pick GPT-5.6 Sol if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 23 shared benchmark results across 7 evidence categories; 4 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 66.79. 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 21. The single biggest benchmark swing on the page is FrontierMath v2 (Tier 4), 6.250% to 83.000%.

GPT-5.6 Sol is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $0.20 input / $1.25 output per 1M tokens for GPT-5.4 nano. That is roughly 24.0x on output cost alone. GPT-5.6 Sol gives you the larger context window at 1M, compared with 400K for GPT-5.4 nano.

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-5.4 nano and GPT-5.6 Sol
CategoryGPT-5.4 nanoΔGPT-5.6 Sol
MathGPT-5.4 nano21.0Margin→ 66.5GPT-5.6 Sol87.5
KnowledgeGPT-5.4 nano43.8Margin→ 50.8GPT-5.6 Sol94.6
AgenticGPT-5.4 nano42.9Margin→ 49.1GPT-5.6 Sol92.0
MultimodalGPT-5.4 nano66.1Margin→ 16.9GPT-5.6 Sol83.0
CodingGPT-5.4 nanoNot measuredMarginNo overlapGPT-5.6 Sol64.6

Decisive benchmark drivers

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

More
A · GPT-5.4 nanoB · GPT-5.6 Sol

  1. FrontierMath v2 (Tier 4)

    Math
    Source ↗
    A 6.250%B 83.000%
    Winner: GPT-5.6 SolΔ 76.8
    FrontierMath v2 (Tier 4): GPT-5.4 nano scored 6.250%; GPT-5.6 Sol scored 83.000%. GPT-5.6 Sol wins this benchmark.

  2. FrontierMath v2 (Tiers 1-3)

    Math
    Source ↗
    A 25.860%B 89.000%
    Winner: GPT-5.6 SolΔ 63.1
    FrontierMath v2 (Tiers 1-3): GPT-5.4 nano scored 25.860%; GPT-5.6 Sol scored 89.000%. GPT-5.6 Sol wins this benchmark.

  3. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 46.3%B 91.9%
    Winner: GPT-5.6 SolΔ 45.6
    Terminal-Bench 2.0: GPT-5.4 nano scored 46.3%; GPT-5.6 Sol scored 91.9%. GPT-5.6 Sol wins this benchmark.

  4. MMMU-Pro

    Multimodal
    Source ↗
    A 66.1%B 83%
    Winner: GPT-5.6 SolΔ 16.9
    MMMU-Pro: GPT-5.4 nano scored 66.1%; GPT-5.6 Sol scored 83%. GPT-5.6 Sol wins this benchmark.

  5. GPQA

    Knowledge
    Source ↗
    A 82.8%B 94.6%
    Winner: GPT-5.6 SolΔ 11.8
    GPQA: GPT-5.4 nano scored 82.8%; 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.

MetricGPT-5.4 nanoGPT-5.6 SolComparison
Input / output priceUSD per 1M tokensGPT-5.4 nano$0.2 input / $1.25 outputGPT-5.6 Sol$5 input / $30 outputGPT-5.4 nano has the lower combined listed price.
Generation speedtokens per secondGPT-5.4 nano191 tok/sGPT-5.6 SolNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGPT-5.4 nano3.64 sGPT-5.6 SolNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGPT-5.4 nano400KGPT-5.6 Sol1MGPT-5.6 Sol lists the larger context window.

Benchmark Deep Dive

AgenticGPT-5.6 Sol wins
BenchmarkGPT-5.4 nanoGPT-5.6 SolResult
Terminal-Bench 2.0Source 46.3%91.9%GPT-5.6 Sol leads
OSWorld-VerifiedSource 39%—Not comparable
MCP AtlasSource 56.1%—Not comparable
ToolathlonSource 35.5%58%GPT-5.6 Sol leads
τ²-bench resultsSource 76%85.1%GPT-5.6 Sol leads
AA Agentic IndexSource 27.5%54.0%GPT-5.6 Sol leads
APEX-Agents-AASource 24.9%—Not comparable
GDPval-AASource 30.0%61.8%GPT-5.6 Sol leads
GDPval-AASource 11001736GPT-5.6 Sol leads
BrowseCompSource —92.2%Not comparable
OSWorld 2.0Source —62.6%Not comparable
CyberGymSource —84.5%Not comparable
ExploitGymSource —33.7%Not comparable
AA BriefcaseSource —1501Not 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
BenchmarkGPT-5.4 nanoGPT-5.6 SolResult
Vibe Code BenchSource 26.10%—Not comparable
AA Coding IndexSource 56.1%77.4%GPT-5.6 Sol leads
AA-SciCodeSource 46.9%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
BenchmarkGPT-5.4 nanoGPT-5.6 SolResult
AA-LCRSource 66.0%73.7%GPT-5.6 Sol leads
CritPtSource 9.3%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
BenchmarkGPT-5.4 nanoGPT-5.6 SolResult
GPQASource 82.8%94.6%GPT-5.6 Sol leads
HLESource 37.7%—Not comparable
HLE w/o toolsSource 24.3%—Not comparable
Artificial Analysis Intelligence IndexSource 38.2%58.9%GPT-5.6 Sol leads
AA-GPQA DiamondSource 81.7%94.1%GPT-5.6 Sol leads
AA-HLESource 26.5%47.2%GPT-5.6 Sol leads
AA-Omniscience IndexSource -29.5%21.7%GPT-5.6 Sol leads
AA-Omniscience AccuracySource 25.4%58.5%GPT-5.6 Sol leads
AA-Omniscience Hallucination RateSource 73.6%88.8%GPT-5.4 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
BenchmarkGPT-5.4 nanoGPT-5.6 SolResult
FrontierMath v2 (Tiers 1-3)Source 25.860%89.000%GPT-5.6 Sol leads
FrontierMath v2 (Tier 4)Source 6.250%83.000%GPT-5.6 Sol leads
FrontierMath (legacy)Source —89%Not comparable
MultimodalGPT-5.6 Sol wins
BenchmarkGPT-5.4 nanoGPT-5.6 SolResult
MMMU-ProSource 66.1%83%GPT-5.6 Sol leads
MMMU-Pro w/ PythonSource 69.5%84.6%GPT-5.6 Sol leads
AA-MMMU-ProSource 65.4%83.4%GPT-5.6 Sol leads
Inst. Following
BenchmarkGPT-5.4 nanoGPT-5.6 SolResult
AA-IFBenchSource 75.9%72.7%GPT-5.4 nano leads
Frequently Asked Questions (5)

Which is better, GPT-5.4 nano or GPT-5.6 Sol?

GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 66.79. The biggest single separator in this matchup is FrontierMath v2 (Tier 4), where the scores are 6.250% and 83.000%.

Which is better for knowledge tasks, GPT-5.4 nano or GPT-5.6 Sol?

GPT-5.6 Sol has the edge for knowledge tasks in this comparison, averaging 94.6 versus 43.8. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.

Which is better for math, GPT-5.4 nano or GPT-5.6 Sol?

GPT-5.6 Sol has the edge for math in this comparison, averaging 87.5 versus 21. Inside this category, FrontierMath v2 (Tier 4) is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, GPT-5.4 nano or GPT-5.6 Sol?

GPT-5.6 Sol has the edge for agentic tasks in this comparison, averaging 92 versus 42.9. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.

Which is better for multimodal and grounded tasks, GPT-5.4 nano or GPT-5.6 Sol?

GPT-5.6 Sol has the edge for multimodal and grounded tasks in this comparison, averaging 83 versus 66.1. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.

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