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Model comparison

GPT-5.6 Sol vs Step 3.7 Flash

Data verified

Head-to-head evidence from 21 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

81.96/100
Margin
31.1pts
← winning
50.87/100
2 category wins0 category wins

Public leaderboard positions: GPT-5.6 Sol #3 (Supported); Step 3.7 Flash #110 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GPT-5.6 Sol and Step 3.7 Flash share 21 comparable benchmark results. 2 of 8 categories are comparable. 25 results are unique to GPT-5.6 Sol; 8 to Step 3.7 Flash.

Updated July 23, 2026
Shared results
21
GPT-5.6 Sol only
25
Step 3.7 Flash only
8
Comparable categories
2 / 8

Pick GPT-5.6 Sol if you want the stronger benchmark profile. Step 3.7 Flash only becomes the better choice if you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 21 shared benchmark results across 6 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 50.87. 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 agentic, where it averages 92 against 66.4. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 91.9% to 59.5%.

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 / $1.15 output per 1M tokens for Step 3.7 Flash. That is roughly 26.1x on output cost alone. GPT-5.6 Sol gives you the larger context window at 1M, compared with 256K for Step 3.7 Flash.

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-5.6 Sol and Step 3.7 Flash
CategoryGPT-5.6 SolΔStep 3.7 Flash
AgenticGPT-5.6 Sol92.0Margin← 25.6Step 3.7 Flash66.4
CodingGPT-5.6 Sol64.6Margin← 8.3Step 3.7 Flash56.3
KnowledgeGPT-5.6 Sol94.6MarginNo overlapStep 3.7 FlashNot measured
MathGPT-5.6 Sol87.5MarginNo overlapStep 3.7 FlashNot measured
MultimodalGPT-5.6 Sol83.0MarginNo overlapStep 3.7 FlashNot measured

Decisive benchmark drivers

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

More
A · GPT-5.6 SolB · Step 3.7 Flash

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 91.9%B 59.5%
    Winner: GPT-5.6 SolΔ 32.4
    Terminal-Bench 2.0: GPT-5.6 Sol scored 91.9%; Step 3.7 Flash scored 59.5%. GPT-5.6 Sol wins this benchmark.

  2. BrowseComp

    Agentic
    Source ↗
    A 92.2%B 75.8%
    Winner: GPT-5.6 SolΔ 16.4
    BrowseComp: GPT-5.6 Sol scored 92.2%; Step 3.7 Flash scored 75.8%. GPT-5.6 Sol wins this benchmark.

  3. SWE-bench Pro

    Coding
    Source ↗
    A 64.6%B 56.3%
    Winner: GPT-5.6 SolΔ 8.3
    SWE-bench Pro: GPT-5.6 Sol scored 64.6%; Step 3.7 Flash scored 56.3%. 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-5.6 SolStep 3.7 FlashComparison
Input / output priceUSD per 1M tokensGPT-5.6 Sol$5 input / $30 outputStep 3.7 Flash$0.2 input / $1.15 outputStep 3.7 Flash has the lower combined listed price.
Generation speedtokens per secondGPT-5.6 SolNot availableStep 3.7 FlashNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGPT-5.6 SolNot availableStep 3.7 FlashNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGPT-5.6 Sol1MStep 3.7 Flash256KGPT-5.6 Sol lists the larger context window.

Benchmark Deep Dive

AgenticGPT-5.6 Sol wins
BenchmarkGPT-5.6 SolStep 3.7 FlashResult
Terminal-Bench 2.0Source 91.9%59.5%GPT-5.6 Sol leads
BrowseCompSource 92.2%75.8%GPT-5.6 Sol leads
OSWorld 2.0Source 62.6%—Not comparable
CyberGymSource 84.5%—Not comparable
ExploitGymSource 33.7%—Not comparable
ToolathlonSource 58%49.5%GPT-5.6 Sol leads
AA Agentic IndexSource 54.0%21.5%GPT-5.6 Sol leads
τ²-bench resultsSource 85.1%98.5%Step 3.7 Flash leads
GDPval-AASource 61.8%25.9%GPT-5.6 Sol leads
GDPval-AASource 17361017GPT-5.6 Sol leads
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
DeepSearchQASource —92.8%Not comparable
Claw-EvalSource —67.1%Not comparable
HLE w/ toolsSource —47.2%Not comparable
Gert LabsSource —51.57%Not comparable
APEX-Agents-AASource —14.8%Not comparable
CodingGPT-5.6 Sol wins
BenchmarkGPT-5.6 SolStep 3.7 FlashResult
SWE-bench ProSource 64.6%56.3%GPT-5.6 Sol leads
Terminal-Bench 2.0Source 91.9%59.5%GPT-5.6 Sol leads
deepSweSource 72.7%—Not comparable
FrontierCode 1.1 ExtendedSource 60.6%—Not comparable
cursorBench32Source 67.2%—Not comparable
VulcanBench v3Source 87.0%—Not comparable
AA Coding IndexSource 77.4%39.6%GPT-5.6 Sol leads
AA-SciCodeSource 56.1%40.0%GPT-5.6 Sol leads
Reasoning
BenchmarkGPT-5.6 SolStep 3.7 FlashResult
ARC-AGI-3Source 7.8%—Not comparable
GeneBench-ProSource 28.7%—Not comparable
AA-LCRSource 73.7%63.7%GPT-5.6 Sol leads
CritPtSource 32.3%2.3%GPT-5.6 Sol leads
Knowledge
BenchmarkGPT-5.6 SolStep 3.7 FlashResult
GPQASource 94.6%—Not comparable
GPQA-DSource 94.6%—Not comparable
HealthBench ProfessionalSource 60.5%—Not comparable
HealthBench HardSource 33.1%—Not comparable
Artificial Analysis Intelligence IndexSource 58.9%30.3%GPT-5.6 Sol leads
AA-GPQA DiamondSource 94.1%80.9%GPT-5.6 Sol leads
AA-HLESource 47.2%19.9%GPT-5.6 Sol leads
AA-Omniscience IndexSource 21.7%-37.5%GPT-5.6 Sol leads
AA-Omniscience AccuracySource 58.5%25.4%GPT-5.6 Sol leads
AA-Omniscience Hallucination RateSource 88.8%84.4%Step 3.7 Flash leads
Math
BenchmarkGPT-5.6 SolStep 3.7 FlashResult
FrontierMath (legacy)Source 89%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 89.000%—Not comparable
FrontierMath v2 (Tier 4)Source 83.000%—Not comparable
Multimodal
BenchmarkGPT-5.6 SolStep 3.7 FlashResult
MMMU-ProSource 83%—Not comparable
MMMU-Pro w/ PythonSource 84.6%—Not comparable
AA-MMMU-ProSource 83.4%75.3%GPT-5.6 Sol leads
SimpleVQASource —79.2%Not comparable
V*Source —95.3%Not comparable
Design Arena WebsiteSource —1211Not comparable
Inst. Following
BenchmarkGPT-5.6 SolStep 3.7 FlashResult
AA-IFBenchSource 72.7%67.3%GPT-5.6 Sol leads
Frequently Asked Questions (3)

Which is better, GPT-5.6 Sol or Step 3.7 Flash?

GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 50.87. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 91.9% and 59.5%.

Which is better for coding, GPT-5.6 Sol or Step 3.7 Flash?

GPT-5.6 Sol has the edge for coding in this comparison, averaging 64.6 versus 56.3. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, GPT-5.6 Sol or Step 3.7 Flash?

GPT-5.6 Sol has the edge for agentic tasks in this comparison, averaging 92 versus 66.4. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.

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