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Model comparison

DeepSeek V3.1 (Reasoning) vs GPT-5.6 Sol

Data verified

Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

53.43/100
Margin
28.5pts
winning →
81.96/100
0 category wins0 category wins

Public leaderboard positions: DeepSeek V3.1 (Reasoning) #97 (Supported); GPT-5.6 Sol #3 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V3.1 (Reasoning) and GPT-5.6 Sol share 11 comparable benchmark results. 0 of 8 categories are comparable. 1 result is unique to DeepSeek V3.1 (Reasoning); 35 to GPT-5.6 Sol.

Updated July 23, 2026
Shared results
11
DeepSeek V3.1 (Reasoning) only
1
GPT-5.6 Sol only
35
Comparable categories
0 / 8

Benchmark data for DeepSeek V3.1 (Reasoning) and GPT-5.6 Sol is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

GPT-5.6 Sol is priced at $5.00 input / $30.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for DeepSeek V3.1 (Reasoning). GPT-5.6 Sol has the larger context window at 1M, compared with 128K for DeepSeek V3.1 (Reasoning).

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 DeepSeek V3.1 (Reasoning) and GPT-5.6 Sol
CategoryDeepSeek V3.1 (Reasoning)ΔGPT-5.6 Sol
AgenticDeepSeek V3.1 (Reasoning)Not measuredMarginNo overlapGPT-5.6 Sol92.0
CodingDeepSeek V3.1 (Reasoning)Not measuredMarginNo overlapGPT-5.6 Sol64.6
KnowledgeDeepSeek V3.1 (Reasoning)Not measuredMarginNo overlapGPT-5.6 Sol94.6
MathDeepSeek V3.1 (Reasoning)Not measuredMarginNo overlapGPT-5.6 Sol87.5
MultimodalDeepSeek V3.1 (Reasoning)Not measuredMarginNo overlapGPT-5.6 Sol83.0

Operational comparison

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

MetricDeepSeek V3.1 (Reasoning)GPT-5.6 SolComparison
Input / output priceUSD per 1M tokensDeepSeek V3.1 (Reasoning)$0 input / $0 outputGPT-5.6 Sol$5 input / $30 outputDeepSeek V3.1 (Reasoning) has the lower combined listed price.
Generation speedtokens per secondDeepSeek V3.1 (Reasoning)Not availableGPT-5.6 SolNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenDeepSeek V3.1 (Reasoning)Not availableGPT-5.6 SolNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensDeepSeek V3.1 (Reasoning)128KGPT-5.6 Sol1MGPT-5.6 Sol lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkDeepSeek V3.1 (Reasoning)GPT-5.6 SolResult
τ²-bench resultsSource 37.4%85.1%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 Agentic IndexSource 54.0%Not comparable
GDPval-AASource 61.8%Not comparable
GDPval-AASource 1736Not 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
BenchmarkDeepSeek V3.1 (Reasoning)GPT-5.6 SolResult
AA-SciCodeSource 39.1%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
AA Coding IndexSource 77.4%Not comparable
Reasoning
BenchmarkDeepSeek V3.1 (Reasoning)GPT-5.6 SolResult
AA-LCRSource 53.3%73.7%GPT-5.6 Sol leads
CritPtSource 2.0%32.3%GPT-5.6 Sol leads
ARC-AGI-3Source 7.8%Not comparable
GeneBench-ProSource 28.7%Not comparable
Knowledge
BenchmarkDeepSeek V3.1 (Reasoning)GPT-5.6 SolResult
Artificial Analysis Intelligence IndexSource 20.7%58.9%GPT-5.6 Sol leads
AA-GPQA DiamondSource 77.9%94.1%GPT-5.6 Sol leads
AA-HLESource 13.0%47.2%GPT-5.6 Sol leads
AA-Omniscience IndexSource -28.4%21.7%GPT-5.6 Sol leads
AA-Omniscience AccuracySource 28.8%58.5%GPT-5.6 Sol leads
AA-Omniscience Hallucination RateSource 80.3%88.8%DeepSeek V3.1 (Reasoning) leads
GPQASource 94.6%Not comparable
GPQA-DSource 94.6%Not comparable
HealthBench ProfessionalSource 60.5%Not comparable
HealthBench HardSource 33.1%Not comparable
Math
BenchmarkDeepSeek V3.1 (Reasoning)GPT-5.6 SolResult
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
BenchmarkDeepSeek V3.1 (Reasoning)GPT-5.6 SolResult
Design Arena WebsiteSource 1152Not comparable
MMMU-ProSource 83%Not comparable
MMMU-Pro w/ PythonSource 84.6%Not comparable
AA-MMMU-ProSource 83.4%Not comparable
Inst. Following
BenchmarkDeepSeek V3.1 (Reasoning)GPT-5.6 SolResult
AA-IFBenchSource 41.5%72.7%GPT-5.6 Sol leads
Frequently Asked Questions (3)

Can I compare DeepSeek V3.1 (Reasoning) and GPT-5.6 Sol on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for DeepSeek V3.1 (Reasoning) and GPT-5.6 Sol today?

DeepSeek V3.1 (Reasoning): $0.00 input / $0.00 output per 1M tokens GPT-5.6 Sol: $5.00 input / $30.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

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Last updated: July 23, 2026

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