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DeepSeek V3.1 Terminus vs DeepSeek V3.2

DeepSeek V3.2 leads DeepSeek V3.1 Terminus on the Artificial Analysis Intelligence Index, 21.5 to 14.8, at about the same output price ($0.88 vs $1.0142 per million). Updated October 21, 2026; 41 benchmarks have a result for both.

Replace DeepSeek V3.1 Terminus Replace DeepSeek V3.2
DeepSeek V3.1 TerminusDeepSeek
Coding
No data
Overall
No data
Output $/M
$1.0142
14
DeepSeek V3.2DeepSeek
Coding
30.0
Overall
37.9
Output $/M
$0.88
27
vs boards won of 41 shared

DeepSeek V3.1 Terminus or DeepSeek V3.2: which to pick

Only DeepSeek V3.2 has a coding score, 30.0 on the Vibe Coding Index; DeepSeek V3.1 Terminus has none, so the two cannot be ranked on coding.

Pick DeepSeek V3.1 Terminus for work measured by LMArena Text: science or LMArena Text: medicine and healthcare, where it leads.

Model ADeepSeek V3.1 TerminusDeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BDeepSeek V3.2DeepSeek30.0/1003 independent benchmarks$0.99 per solved task
Shared results
41
DeepSeek V3.1 Terminus only
4
DeepSeek V3.2 only
34
Like-for-like categories
8 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
DeepSeek V3.1 Terminus not benchmarked, DeepSeek V3.2 30.0 from 3 benchmarks.
Widest category
Agentic work, 53.5 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: DeepSeek V3.1 Terminus 37.1% against DeepSeek V3.2 90.6%, 53.5 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.1 Terminus $1.0142 against DeepSeek V3.2 $0.88 per million output tokens, 1.2x apart.
Context window
Both take 164K tokens.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryDeepSeek V3.1 TerminusBarsDeepSeek V3.2Ties
Coding05
Intelligence01
Agentic work01
Reasoning04
Math03
Knowledge41
Web design61
General411
All shared boards1427
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
Coding benchmarks for DeepSeek V3.1 Terminus and DeepSeek V3.2
BenchmarkDeepSeek V3.1 TerminusDeepSeek V3.2Leader
SWE-bench VerifiedNot measured70.0%Only DeepSeek V3.2 measured
SWE-bench MultilingualNot measured59.0%Only DeepSeek V3.2 measured
LMArena WebDevNot measured1362Only DeepSeek V3.2 measured
AA Coding Index43.544.2DeepSeek V3.2
LiveCodeBench (Vals AI)Not measured80.7%Only DeepSeek V3.2 measured
SWE-bench Verified (Vals AI)Not measured67.6%Only DeepSeek V3.2 measured
Vibe Code Bench (Vals AI)Not measured5.1%Only DeepSeek V3.2 measured
LiveCodeBench (Artificial Analysis run)79.8%86.2%DeepSeek V3.2
SciCode38.0%Not measuredOnly DeepSeek V3.1 Terminus measured
Terminal-Bench Hard (Artificial Analysis run)31.8%35.6%DeepSeek V3.2
Terminal-BenchNot measured39.6%Only DeepSeek V3.2 measured
ALE-Bench745.2Not measuredOnly DeepSeek V3.1 Terminus measured
LMArena Text: coding14251453DeepSeek V3.2
LMArena Text: software and IT14261449DeepSeek V3.2
LMArena WebDev: ReactNot measured1350Only DeepSeek V3.2 measured
LMArena WebDev: HTMLNot measured1371Only DeepSeek V3.2 measured
Neither model has a result on the other 23 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for DeepSeek V3.1 Terminus and DeepSeek V3.2
BenchmarkDeepSeek V3.1 TerminusDeepSeek V3.2Leader
AA Intelligence Index14.821.5DeepSeek V3.2
Epoch Capabilities IndexNot measured146.1Only DeepSeek V3.2 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for DeepSeek V3.1 Terminus and DeepSeek V3.2
BenchmarkDeepSeek V3.1 TerminusDeepSeek V3.2Leader
AA Agentic Index6.8Not measuredOnly DeepSeek V3.1 Terminus measured
τ²-Bench Telecom37.1%90.6%DeepSeek V3.2
APEX-AgentsNot measured21.3%Only DeepSeek V3.2 measured
Vending-Bench 2Not measured$1,034Only DeepSeek V3.2 measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for DeepSeek V3.1 Terminus and DeepSeek V3.2
BenchmarkDeepSeek V3.1 TerminusDeepSeek V3.2Leader
GPQA DiamondNot measured80.3%Only DeepSeek V3.2 measured
GPQA Diamond (Artificial Analysis run)79.2%84.0%DeepSeek V3.2
Humanity's Last Exam (Artificial Analysis run)16.4%24.6%DeepSeek V3.2
ARC-AGINot measured57.0%Only DeepSeek V3.2 measured
ARC-AGI-2Not measured4.0%Only DeepSeek V3.2 measured
LMArena Text: hard prompts14261434DeepSeek V3.2
LMArena Text: expertNot measured1436Only DeepSeek V3.2 measured
LMArena Text: hard prompts in English14321446DeepSeek V3.2
Kagi LLM Benchmark57.4%Not measuredOnly DeepSeek V3.1 Terminus measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for DeepSeek V3.1 Terminus and DeepSeek V3.2
BenchmarkDeepSeek V3.1 TerminusDeepSeek V3.2Leader
AIMENot measured84.6%Only DeepSeek V3.2 measured
MGSM (Vals AI)Not measured86.0%Only DeepSeek V3.2 measured
AA Math Index89.792.0DeepSeek V3.2
AIME 2025 (Artificial Analysis run)89.7%92.0%DeepSeek V3.2
LMArena Text: math14021435DeepSeek V3.2
LMArena Text: mathematical workNot measured1440Only DeepSeek V3.2 measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
Knowledge benchmarks for DeepSeek V3.1 Terminus and DeepSeek V3.2
BenchmarkDeepSeek V3.1 TerminusDeepSeek V3.2Leader
MMLU ProNot measured84.9%Only DeepSeek V3.2 measured
LegalBench (Vals AI)Not measured76.1%Only DeepSeek V3.2 measured
CaseLaw (Vals AI)Not measured55.4%Only DeepSeek V3.2 measured
CorpFin (Vals AI)Not measured51.0%Only DeepSeek V3.2 measured
TaxEval (Vals AI)Not measured68.2%Only DeepSeek V3.2 measured
MedQA (Vals AI)Not measured93.9%Only DeepSeek V3.2 measured
MMLU Pro (Artificial Analysis run)85.1%86.2%DeepSeek V3.2
LMArena Text: science14511446DeepSeek V3.1 Terminus
LMArena Text: medicine and healthcare14681440DeepSeek V3.1 Terminus
LMArena Text: legal and government14571425DeepSeek V3.1 Terminus
LMArena Text: business and finance14141410DeepSeek V3.1 Terminus
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index61
Web design benchmarks for DeepSeek V3.1 Terminus and DeepSeek V3.2
BenchmarkDeepSeek V3.1 TerminusDeepSeek V3.2Leader
Design Arena: websites11871175DeepSeek V3.1 Terminus
Design Arena: UI components11821149DeepSeek V3.1 Terminus
Design Arena: game dev11311132DeepSeek V3.2
Design Arena: data viz11671158DeepSeek V3.1 Terminus
Design Arena: 3D11411133DeepSeek V3.1 Terminus
Design Arena: all code categories11751164DeepSeek V3.1 Terminus
Design Arena: SVG10651032DeepSeek V3.1 Terminus
Design Arena: ASCII artNot measured1083Only DeepSeek V3.2 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index411
General benchmarks for DeepSeek V3.1 Terminus and DeepSeek V3.2
BenchmarkDeepSeek V3.1 TerminusDeepSeek V3.2Leader
IFBench57.0%60.7%DeepSeek V3.2
Long context reasoning (AA-LCR)69.3%73.3%DeepSeek V3.2
DTBench81.3%85.6%DeepSeek V3.2
LMCA28.6%28.8%DeepSeek V3.2
CL-benchNot measured12.4%Only DeepSeek V3.2 measured
CL-bench LifeNot measured7.4%Only DeepSeek V3.2 measured
LMArena Text14191425DeepSeek V3.2
LMArena Text: instruction following14041413DeepSeek V3.2
LMArena Text: creative writing14031400DeepSeek V3.1 Terminus
LMArena Text: English14291439DeepSeek V3.2
LMArena Text: non-English14081409DeepSeek V3.2
LMArena Text: ChineseNot measured1455Only DeepSeek V3.2 measured
LMArena Text: GermanNot measured1413Only DeepSeek V3.2 measured
LMArena Text: JapaneseNot measured1374Only DeepSeek V3.2 measured
LMArena Text: KoreanNot measured1370Only DeepSeek V3.2 measured
LMArena Text: FrenchNot measured1429Only DeepSeek V3.2 measured
LMArena Text: SpanishNot measured1424Only DeepSeek V3.2 measured
LMArena Text: Russian14351424DeepSeek V3.1 Terminus
LMArena Text: Polish14271419DeepSeek V3.1 Terminus
LMArena Text: multi-turn14111427DeepSeek V3.2
LMArena Text: longer queries14221428DeepSeek V3.2
LMArena Text: writing and language14091407DeepSeek V3.1 Terminus
LMArena Text: entertainment and media13911395DeepSeek V3.2
Neither model has a result on the other 23 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.1 Terminus and DeepSeek V3.2
BenchmarkDeepSeek V3.1 TerminusDeepSeek V3.2Leader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

DeepSeek V3.1 Terminus$0.0008Fits in one request
DeepSeek V3.2$0.0007Fits in one request

DeepSeek V3.2 costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.1 Terminus$0.018Fits in one request
DeepSeek V3.2$0.017Fits in one request

DeepSeek V3.2 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.1 Terminus$0.071Exceeds the context window
DeepSeek V3.2$0.067Exceeds the context window

DeepSeek V3.2 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of DeepSeek V3.1 Terminus and DeepSeek V3.2
SpecificationDeepSeek V3.1 TerminusDeepSeek V3.2
MakerDeepSeekDeepSeek
WeightsOpen weightsOpen weights
ReleasedSeptember 22, 2025December 1, 2025
Context window164K164K
Input $/Mtok$0.3063$0.29
Output $/Mtok$1.0142$0.88
Coding indexNot benchmarked30.0
Independent measurements behind it03
Cost per solved taskNot computable$0.99
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.1 Terminus better than DeepSeek V3.2 for coding?

Only DeepSeek V3.2 has a coding score, 30.0 on the Vibe Coding Index; DeepSeek V3.1 Terminus has none, so the two cannot be ranked on coding. Pick DeepSeek V3.1 Terminus for work measured by LMArena Text: science or LMArena Text: medicine and healthcare, where it leads.

Which is cheaper, DeepSeek V3.1 Terminus or DeepSeek V3.2?

DeepSeek V3.1 Terminus costs $0.3063 per million input tokens and $1.0142 per million output tokens; DeepSeek V3.2 costs $0.29 and $0.88. Cost per solved task is known for DeepSeek V3.2 only.

Which has the bigger context window, DeepSeek V3.1 Terminus or DeepSeek V3.2?

Neither: both take 164K tokens.

How many benchmarks is the DeepSeek V3.1 Terminus vs DeepSeek V3.2 comparison based on?

41 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.1 Terminus's coding index rests on 0 independent benchmarks and DeepSeek V3.2's on 3. Where only one model has a result, the page says so instead of naming a winner.

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