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DeepSeek V3.2 Exp vs Qwen3.7 Plus

Qwen3.7 Plus leads DeepSeek V3.2 Exp on the Artificial Analysis Intelligence Index, 25.2 to 16.6, and DeepSeek V3.2 Exp costs 3.1x less per output token ($0.41 vs $1.28 per million). Updated October 21, 2026; 45 benchmarks have a result for both.

Replace DeepSeek V3.2 Exp Replace Qwen3.7 Plus
DeepSeek V3.2 ExpDeepSeek
Coding
No data
Overall
16.6
Output $/M
$0.41
2
Qwen3.7 PlusQwen
Coding
33.2
Overall
25.2
Output $/M
$1.28
43
vs boards won of 45 shared

DeepSeek V3.2 Exp or Qwen3.7 Plus: which to pick

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; DeepSeek V3.2 Exp has none, so the two cannot be ranked on coding.

Pick DeepSeek V3.2 Exp for output tokens 3.1x cheaper ($0.41 vs $1.28 per million) and work measured by LMArena Text: medicine and healthcare or DTBench, where it leads.

Model ADeepSeek V3.2 ExpDeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BQwen3.7 PlusQwen33.2/1002 independent benchmarksNo cost per solved task
Shared results
45
DeepSeek V3.2 Exp only
12
Qwen3.7 Plus only
30
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 V3.2 Exp not benchmarked, Qwen3.7 Plus 33.2 from 2 benchmarks.
Widest category
Agentic work, 59.1 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: DeepSeek V3.2 Exp 33.9% against Qwen3.7 Plus 93.0%, 59.1 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 Exp $0.41 against Qwen3.7 Plus $1.28 per million output tokens, 3.1x apart.
Context window
DeepSeek V3.2 Exp takes 164K tokens, Qwen3.7 Plus 1M.

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 V3.2 ExpBarsQwen3.7 PlusTies
Coding03
Intelligence02
Agentic work01
Reasoning05
Math02
Knowledge13
Web design07
General120
All shared boards243
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for DeepSeek V3.2 Exp and Qwen3.7 Plus
BenchmarkDeepSeek V3.2 ExpQwen3.7 PlusLeader
Aider polyglot74.2%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena WebDev1272Not measuredOnly DeepSeek V3.2 Exp measured
AA Coding IndexNot measured55.9Only Qwen3.7 Plus measured
Vibe Code Bench (Vals AI)Not measured46.4%Only Qwen3.7 Plus measured
Code migration (Vals AI)Not measured12.9%Only Qwen3.7 Plus measured
Terminal-Bench 2.1 (Vals AI)Not measured52.8%Only Qwen3.7 Plus measured
SkillsBench (Vals AI)Not measured54.3%Only Qwen3.7 Plus measured
LiveCodeBench (Artificial Analysis run)78.9%Not measuredOnly DeepSeek V3.2 Exp measured
SciCodeNot measured46.1%Only Qwen3.7 Plus measured
Terminal-Bench Hard (Artificial Analysis run)31.1%47.0%Qwen3.7 Plus
FrontierCodeNot measured10.2%Only Qwen3.7 Plus measured
WeirdML39.5%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: coding14381473Qwen3.7 Plus
LMArena Text: software and IT14381473Qwen3.7 Plus
LMArena WebDev: HTML1281Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 23 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for DeepSeek V3.2 Exp and Qwen3.7 Plus
BenchmarkDeepSeek V3.2 ExpQwen3.7 PlusLeader
AA Intelligence Index16.625.2Qwen3.7 Plus
Epoch Capabilities Index144.9147.0Qwen3.7 Plus
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for DeepSeek V3.2 Exp and Qwen3.7 Plus
BenchmarkDeepSeek V3.2 ExpQwen3.7 PlusLeader
AA Agentic IndexNot measured17.5Only Qwen3.7 Plus measured
Finance Agent (Vals AI)Not measured38.2%Only Qwen3.7 Plus measured
Tax Agent Bench (Vals AI)Not measured10.5%Only Qwen3.7 Plus measured
Legal Research Bench (Vals AI)Not measured16.4%Only Qwen3.7 Plus measured
Excel Modeling Benchmark (Vals AI)Not measured49.3%Only Qwen3.7 Plus measured
τ²-Bench Telecom33.9%93.0%Qwen3.7 Plus
OSWorld 2.0Not measured2.8%Only Qwen3.7 Plus measured
TheAgentCompany42.9%Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 31 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for DeepSeek V3.2 Exp and Qwen3.7 Plus
BenchmarkDeepSeek V3.2 ExpQwen3.7 PlusLeader
GPQA Diamond (Artificial Analysis run)79.7%90.0%Qwen3.7 Plus
Humanity's Last Exam (Artificial Analysis run)14.9%35.6%Qwen3.7 Plus
GPQA Diamond (Epoch AI run)Not measured87.9%Only Qwen3.7 Plus measured
Mystery game puzzlesNot measured17.0%Only Qwen3.7 Plus measured
LMArena Text: hard prompts14291460Qwen3.7 Plus
LMArena Text: expert14221466Qwen3.7 Plus
LMArena Text: hard prompts in English14441460Qwen3.7 Plus
LMArena Vision: diagramsNot measured1292Only Qwen3.7 Plus measured
LMArena Vision: homeworkNot measured1295Only Qwen3.7 Plus measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for DeepSeek V3.2 Exp and Qwen3.7 Plus
BenchmarkDeepSeek V3.2 ExpQwen3.7 PlusLeader
AA Math Index87.7Not measuredOnly DeepSeek V3.2 Exp measured
AIME 2025 (Artificial Analysis run)87.7%Not measuredOnly DeepSeek V3.2 Exp measured
OTIS Mock AIMENot measured93.3%Only Qwen3.7 Plus measured
FrontierMath, tiers 1 to 3Not measured34.4%Only Qwen3.7 Plus measured
LMArena Text: math14221467Qwen3.7 Plus
LMArena Text: mathematical work14331470Qwen3.7 Plus
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
Knowledge benchmarks for DeepSeek V3.2 Exp and Qwen3.7 Plus
BenchmarkDeepSeek V3.2 ExpQwen3.7 PlusLeader
MortgageTax (Vals AI)Not measured66.2%Only Qwen3.7 Plus measured
MMLU Pro (Artificial Analysis run)85.0%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: science14431464Qwen3.7 Plus
LMArena Text: medicine and healthcare14681464DeepSeek V3.2 Exp
LMArena Text: legal and government14191451Qwen3.7 Plus
LMArena Text: business and finance14121435Qwen3.7 Plus
Neither model has a result on the other 11 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for DeepSeek V3.2 Exp and Qwen3.7 Plus
BenchmarkDeepSeek V3.2 ExpQwen3.7 PlusLeader
Design Arena: websites11791269Qwen3.7 Plus
Design Arena: UI components11671261Qwen3.7 Plus
Design Arena: game dev11441262Qwen3.7 Plus
Design Arena: data viz11521276Qwen3.7 Plus
Design Arena: 3D11481239Qwen3.7 Plus
Design Arena: all code categories11711269Qwen3.7 Plus
Design Arena: SVG10321208Qwen3.7 Plus
Design Arena: ASCII artNot measured1143Only Qwen3.7 Plus measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index120
General benchmarks for DeepSeek V3.2 Exp and Qwen3.7 Plus
BenchmarkDeepSeek V3.2 ExpQwen3.7 PlusLeader
SAGE (Vals AI)Not measured39.3%Only Qwen3.7 Plus measured
Vals Multimodal IndexNot measured53.9%Only Qwen3.7 Plus measured
IFBench54.1%78.0%Qwen3.7 Plus
Long context reasoning (AA-LCR)72.3%73.0%Qwen3.7 Plus
DTBench87.7%84.0%DeepSeek V3.2 Exp
LMCA29.1%37.6%Qwen3.7 Plus
Fiction.LiveBench83.3%Not measuredOnly DeepSeek V3.2 Exp measured
CL-bench13.2%Not measuredOnly DeepSeek V3.2 Exp measured
CL-bench Life9.5%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text14251454Qwen3.7 Plus
LMArena Text: instruction following14011439Qwen3.7 Plus
LMArena Text: creative writing14041438Qwen3.7 Plus
LMArena VisionNot measured1278Only Qwen3.7 Plus measured
LMArena Text: English14411458Qwen3.7 Plus
LMArena Text: non-English14041445Qwen3.7 Plus
LMArena Text: Chinese14611509Qwen3.7 Plus
LMArena Text: German14401471Qwen3.7 Plus
LMArena Text: Japanese13311412Qwen3.7 Plus
LMArena Text: Korean13721413Qwen3.7 Plus
LMArena Text: French14341472Qwen3.7 Plus
LMArena Text: Spanish14411457Qwen3.7 Plus
LMArena Text: Russian14121457Qwen3.7 Plus
LMArena Text: Polish14351449Qwen3.7 Plus
LMArena Text: multi-turn14221459Qwen3.7 Plus
LMArena Text: longer queries14181454Qwen3.7 Plus
LMArena Text: writing and language14071437Qwen3.7 Plus
LMArena Text: entertainment and media14071422Qwen3.7 Plus
LMArena Vision: EnglishNot measured1280Only Qwen3.7 Plus measured
LMArena Vision: ChineseNot measured1332Only Qwen3.7 Plus measured
LMArena Vision: reading textNot measured1288Only Qwen3.7 Plus measured
LMArena Vision: humorNot measured1261Only Qwen3.7 Plus measured
LMArena Vision: creative writingNot measured1258Only Qwen3.7 Plus measured
LMArena DocumentNot measured1444Only Qwen3.7 Plus measured
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.2 Exp and Qwen3.7 Plus
BenchmarkDeepSeek V3.2 ExpQwen3.7 PlusLeader
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 V3.2 Exp$0.0005Fits in one request
Qwen3.7 Plus$0.0010Fits in one request

DeepSeek V3.2 Exp costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2 Exp$0.015Fits in one request
Qwen3.7 Plus$0.020Fits in one request

DeepSeek V3.2 Exp costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2 Exp$0.058Exceeds the context window
Qwen3.7 Plus$0.077Fits in one request

DeepSeek V3.2 Exp 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 V3.2 Exp and Qwen3.7 Plus
SpecificationDeepSeek V3.2 ExpQwen3.7 Plus
MakerDeepSeekQwen
WeightsOpen weightsNo public weights listed
ReleasedSeptember 29, 2025June 3, 2026
Context window164K1M
Input $/Mtok$0.27$0.32
Output $/Mtok$0.41$1.28
Coding indexNot benchmarked33.2
Independent measurements behind it12
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 Exp better than Qwen3.7 Plus for coding?

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; DeepSeek V3.2 Exp has none, so the two cannot be ranked on coding. Pick DeepSeek V3.2 Exp for output tokens 3.1x cheaper ($0.41 vs $1.28 per million) and work measured by LMArena Text: medicine and healthcare or DTBench, where it leads.

Which is cheaper, DeepSeek V3.2 Exp or Qwen3.7 Plus?

DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V3.2 Exp or Qwen3.7 Plus?

Qwen3.7 Plus, with 1M tokens against 164K.

How many benchmarks is the DeepSeek V3.2 Exp vs Qwen3.7 Plus comparison based on?

45 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.2 Exp's coding index rests on 1 independent benchmark and Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.

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