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DeepSeek V3.2 Exp vs Qwen3.5 397B A17B

Updated October 21, 2026. 47 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace DeepSeek V3.2 Exp Replace Qwen3.5 397B A17B
DeepSeek V3.2 ExpDeepSeek
Coding
55.0
Overall
16.6
Output $/M
$0.41
7
Qwen3.5 397B A17BQwen
Coding
28.6
Overall
21.4
Output $/M
$2.34
40
vs boards won of 47 shared

Decision reading

Pick DeepSeek V3.2 Exp for coding: it scores 55.0 on the Vibe Coding Index against 28.6 for Qwen3.5 397B A17B.

Pick Qwen3.5 397B A17B when the context window is larger, 262K against 164K tokens, or when what matters is LMArena WebDev or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Model ADeepSeek V3.2 ExpDeepSeek55.0/1002 independent benchmarksNo cost per solved taskModel BQwen3.5 397B A17BQwen28.6/1001 independent benchmarkNo cost per solved task
Shared results
47
DeepSeek V3.2 Exp only
10
Qwen3.5 397B A17B only
18
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 55.0 from 2 benchmarks, Qwen3.5 397B A17B 28.6 from 1 benchmark.
Widest category
Agentic work, 61.7 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: DeepSeek V3.2 Exp 33.9% against Qwen3.5 397B A17B 95.6%, 61.7 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 Exp $0.41 against Qwen3.5 397B A17B $2.34 per million output tokens, 5.7x apart.
Context window
DeepSeek V3.2 Exp takes 164K tokens, Qwen3.5 397B A17B 262K.

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 ExpBarsQwen3.5 397B A17BTies
Coding05
Intelligence02
Agentic work01
Reasoning05
Math02
Knowledge13
Web design25
General417
All shared boards740
CodingLike-for-likeFour of these boards feed the Vibe Coding Index05
Coding benchmarks for DeepSeek V3.2 Exp and Qwen3.5 397B A17B
BenchmarkDeepSeek V3.2 ExpQwen3.5 397B A17BLeader
Aider polyglot74.2%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena WebDev12721400Qwen3.5 397B A17B
LiveCodeBench (Artificial Analysis run)78.9%Not measuredOnly DeepSeek V3.2 Exp measured
SciCodeNot measured44.8%Only Qwen3.5 397B A17B measured
Terminal-Bench Hard (Artificial Analysis run)31.1%40.9%Qwen3.5 397B A17B
WeirdML39.5%Not measuredOnly DeepSeek V3.2 Exp measured
ALE-BenchNot measured621.9Only Qwen3.5 397B A17B measured
LMArena Text: coding14381464Qwen3.5 397B A17B
LMArena Text: software and IT14381463Qwen3.5 397B A17B
LMArena WebDev: ReactNot measured1388Only Qwen3.5 397B A17B measured
LMArena WebDev: HTML12811410Qwen3.5 397B A17B
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for DeepSeek V3.2 Exp and Qwen3.5 397B A17B
BenchmarkDeepSeek V3.2 ExpQwen3.5 397B A17BLeader
AA Intelligence Index16.621.4Qwen3.5 397B A17B
Epoch Capabilities Index144.9146.8Qwen3.5 397B A17B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for DeepSeek V3.2 Exp and Qwen3.5 397B A17B
BenchmarkDeepSeek V3.2 ExpQwen3.5 397B A17BLeader
τ²-Bench Telecom33.9%95.6%Qwen3.5 397B A17B
APEX-AgentsNot measured24.9%Only Qwen3.5 397B A17B measured
TheAgentCompany42.9%Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for DeepSeek V3.2 Exp and Qwen3.5 397B A17B
BenchmarkDeepSeek V3.2 ExpQwen3.5 397B A17BLeader
GPQA Diamond (Artificial Analysis run)79.7%89.3%Qwen3.5 397B A17B
Humanity's Last Exam (Artificial Analysis run)14.9%29.0%Qwen3.5 397B A17B
GPQA Diamond (Epoch AI run)Not measured86.4%Only Qwen3.5 397B A17B measured
Mystery game puzzlesNot measured18.0%Only Qwen3.5 397B A17B measured
LMArena Text: hard prompts14291448Qwen3.5 397B A17B
LMArena Text: expert14221462Qwen3.5 397B A17B
LMArena Text: hard prompts in English14441450Qwen3.5 397B A17B
LMArena Vision: diagramsNot measured1277Only Qwen3.5 397B A17B measured
LMArena Vision: homeworkNot measured1292Only Qwen3.5 397B A17B 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 Qwen3.5 397B A17B
BenchmarkDeepSeek V3.2 ExpQwen3.5 397B A17BLeader
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 measured88.9%Only Qwen3.5 397B A17B measured
FrontierMath, tiers 1 to 3Not measured31.2%Only Qwen3.5 397B A17B measured
LMArena Text: math14221453Qwen3.5 397B A17B
LMArena Text: mathematical work14331454Qwen3.5 397B A17B
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 Qwen3.5 397B A17B
BenchmarkDeepSeek V3.2 ExpQwen3.5 397B A17BLeader
MMLU Pro (Artificial Analysis run)85.0%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: science14431457Qwen3.5 397B A17B
LMArena Text: medicine and healthcare14681455DeepSeek V3.2 Exp
LMArena Text: legal and government14191441Qwen3.5 397B A17B
LMArena Text: business and finance14121435Qwen3.5 397B A17B
Neither model has a result on the other 12 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index25
Web design benchmarks for DeepSeek V3.2 Exp and Qwen3.5 397B A17B
BenchmarkDeepSeek V3.2 ExpQwen3.5 397B A17BLeader
Design Arena: websites11791191Qwen3.5 397B A17B
Design Arena: UI components11661163DeepSeek V3.2 Exp
Design Arena: game dev11451141DeepSeek V3.2 Exp
Design Arena: data viz11521175Qwen3.5 397B A17B
Design Arena: 3D11481161Qwen3.5 397B A17B
Design Arena: all code categories11711180Qwen3.5 397B A17B
Design Arena: SVG10311139Qwen3.5 397B A17B
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index417
General benchmarks for DeepSeek V3.2 Exp and Qwen3.5 397B A17B
BenchmarkDeepSeek V3.2 ExpQwen3.5 397B A17BLeader
IFBench54.1%78.8%Qwen3.5 397B A17B
Long context reasoning (AA-LCR)72.3%77.3%Qwen3.5 397B A17B
DTBench87.7%87.5%DeepSeek V3.2 Exp
LMCA29.1%37.9%Qwen3.5 397B A17B
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 Text14251437Qwen3.5 397B A17B
LMArena Text: instruction following14011424Qwen3.5 397B A17B
LMArena Text: creative writing14041402DeepSeek V3.2 Exp
LMArena VisionNot measured1262Only Qwen3.5 397B A17B measured
LMArena Text: English14411443Qwen3.5 397B A17B
LMArena Text: non-English14041430Qwen3.5 397B A17B
LMArena Text: Chinese14611498Qwen3.5 397B A17B
LMArena Text: German14401445Qwen3.5 397B A17B
LMArena Text: Japanese13311429Qwen3.5 397B A17B
LMArena Text: Korean13721384Qwen3.5 397B A17B
LMArena Text: French14341462Qwen3.5 397B A17B
LMArena Text: Spanish14411441DeepSeek V3.2 Exp
LMArena Text: Russian14121430Qwen3.5 397B A17B
LMArena Text: Polish14351447Qwen3.5 397B A17B
LMArena Text: multi-turn14221446Qwen3.5 397B A17B
LMArena Text: longer queries14181441Qwen3.5 397B A17B
LMArena Text: writing and language14071415Qwen3.5 397B A17B
LMArena Text: entertainment and media14071399DeepSeek V3.2 Exp
LMArena Vision: EnglishNot measured1268Only Qwen3.5 397B A17B measured
LMArena Vision: ChineseNot measured1314Only Qwen3.5 397B A17B measured
LMArena Vision: reading textNot measured1271Only Qwen3.5 397B A17B measured
LMArena Vision: humorNot measured1262Only Qwen3.5 397B A17B measured
LMArena Vision: captioningNot measured1230Only Qwen3.5 397B A17B measured
LMArena Vision: recognizing thingsNot measured1265Only Qwen3.5 397B A17B measured
LMArena Vision: creative writingNot measured1260Only Qwen3.5 397B A17B measured
Neither model has a result on the other 14 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 Qwen3.5 397B A17B
BenchmarkDeepSeek V3.2 ExpQwen3.5 397B A17BLeader
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
Qwen3.5 397B A17B$0.0016Fits 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
Qwen3.5 397B A17B$0.027Fits 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
Qwen3.5 397B A17B$0.101Fits 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 Qwen3.5 397B A17B
SpecificationDeepSeek V3.2 ExpQwen3.5 397B A17B
MakerDeepSeekQwen
WeightsOpen weightsOpen weights
ReleasedSeptember 29, 2025February 16, 2026
Context window164K262K
Input $/Mtok$0.27$0.39
Output $/Mtok$0.41$2.34
Coding index55.028.6
Independent measurements behind it21
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 Exp better than Qwen3.5 397B A17B for coding?

Pick DeepSeek V3.2 Exp for coding: it scores 55.0 on the Vibe Coding Index against 28.6 for Qwen3.5 397B A17B. Pick Qwen3.5 397B A17B when the context window is larger, 262K against 164K tokens, or when what matters is LMArena WebDev or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Which is cheaper, DeepSeek V3.2 Exp or Qwen3.5 397B A17B?

DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V3.2 Exp or Qwen3.5 397B A17B?

Qwen3.5 397B A17B, with 262K tokens against 164K.

How many benchmarks is the DeepSeek V3.2 Exp vs Qwen3.5 397B A17B comparison based on?

47 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.2 Exp's coding index rests on 2 independent benchmarks and Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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