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Model comparison

DeepSeek V3.1 vs DeepSeek V3.2

Data verified

Head-to-head evidence from 12 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

53.64/100
Margin
1.8pts
winning →
55.4/100
0 category wins0 category wins

Public leaderboard positions: DeepSeek V3.1 #95 (Supported); DeepSeek V3.2 #82 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V3.1 and DeepSeek V3.2 share 12 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to DeepSeek V3.1; 7 to DeepSeek V3.2.

Updated July 20, 2026
Shared results
12
DeepSeek V3.1 only
0
DeepSeek V3.2 only
7
Comparable categories
0 / 8

Benchmark data for DeepSeek V3.1 and DeepSeek V3.2 is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 6 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.

DeepSeek V3.2 is priced at $0.28 input / $0.42 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for DeepSeek V3.1.

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 and DeepSeek V3.2
CategoryDeepSeek V3.1ΔDeepSeek V3.2
CodingDeepSeek V3.1Not measuredMarginNo overlapDeepSeek V3.260.9
MathDeepSeek V3.1Not measuredMarginNo overlapDeepSeek V3.217.1

Operational comparison

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

MetricDeepSeek V3.1DeepSeek V3.2Comparison
Input / output priceUSD per 1M tokensDeepSeek V3.1$0 input / $0 outputDeepSeek V3.2$0.28 input / $0.42 outputDeepSeek V3.1 has the lower combined listed price.
Generation speedtokens per secondDeepSeek V3.1Not availableDeepSeek V3.235 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenDeepSeek V3.1Not availableDeepSeek V3.23.75 sA complete latency comparison is not available.
Context windowmaximum listed tokensDeepSeek V3.1128KDeepSeek V3.2128KListed context windows are equal.

Benchmark Deep Dive

Agentic
BenchmarkDeepSeek V3.1DeepSeek V3.2Result
τ²-bench resultsSource 34.8%78.9%DeepSeek V3.2 leads
Claw-EvalSource 40.2%Not comparable
VITA-BenchSource 18.5%Not comparable
Gert LabsSource 29.57%Not comparable
Coding
BenchmarkDeepSeek V3.1DeepSeek V3.2Result
AA-SciCodeSource 36.7%38.7%DeepSeek V3.2 leads
SWE-RebenchSource 60.9%Not comparable
React Native EvalsSource 71.5%Not comparable
Reasoning
BenchmarkDeepSeek V3.1DeepSeek V3.2Result
AA-LCRSource 45.0%39.0%DeepSeek V3.1 leads
CritPtSource 0.0%0.9%DeepSeek V3.2 leads
Knowledge
BenchmarkDeepSeek V3.1DeepSeek V3.2Result
Artificial Analysis Intelligence IndexSource 21.1%24.7%DeepSeek V3.2 leads
AA-GPQA DiamondSource 73.5%75.1%DeepSeek V3.2 leads
AA-HLESource 6.3%10.5%DeepSeek V3.2 leads
AA-Omniscience IndexSource -41.1%-46.7%DeepSeek V3.1 leads
AA-Omniscience AccuracySource 23.1%24.2%DeepSeek V3.2 leads
AA-Omniscience Hallucination RateSource 83.5%93.5%DeepSeek V3.1 leads
Math
BenchmarkDeepSeek V3.1DeepSeek V3.2Result
FrontierMath v2 (Tiers 1-3)Source 22.100%Not comparable
FrontierMath v2 (Tier 4)Source 2.100%Not comparable
Multimodal
BenchmarkDeepSeek V3.1DeepSeek V3.2Result
Design Arena WebsiteSource 11551206DeepSeek V3.2 leads
Inst. Following
BenchmarkDeepSeek V3.1DeepSeek V3.2Result
AA-IFBenchSource 37.8%49.0%DeepSeek V3.2 leads
Frequently Asked Questions (3)

Can I compare DeepSeek V3.1 and DeepSeek V3.2 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 and DeepSeek V3.2 today?

DeepSeek V3.1: $0.00 input / $0.00 output per 1M tokens DeepSeek V3.2: $0.28 input / $0.42 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 20, 2026

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