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DeepSeek V3.2 Exp vs Qwen3.5-122B-A10B

Updated October 21, 2026. 39 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 Qwen3.5-122B-A10B
DeepSeek V3.2 ExpDeepSeek
Coding
55.0
Overall
16.6
Output $/M
$0.41
22
Qwen3.5-122B-A10BQwen
Coding
22.9
Overall
17.7
Output $/M
$2.08
16
vs boards won of 39 shared, 1 tied

Decision reading

Pick DeepSeek V3.2 Exp for coding: it scores 55.0 on the Vibe Coding Index against 22.9 for Qwen3.5-122B-A10B.

Pick Qwen3.5-122B-A10B when the context window is larger, 262K against 164K tokens, or when what matters is LMArena WebDev or LMArena WebDev: HTML, where it leads.

Model ADeepSeek V3.2 ExpDeepSeek55.0/1002 independent benchmarksNo cost per solved taskModel BQwen3.5-122B-A10BQwen22.9/1001 independent benchmarkNo cost per solved task
Shared results
39
DeepSeek V3.2 Exp only
18
Qwen3.5-122B-A10B only
12
Like-for-like categories
7 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, Qwen3.5-122B-A10B 22.9 from 1 benchmark.
Widest category
Agentic work, 59.6 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: DeepSeek V3.2 Exp 33.9% against Qwen3.5-122B-A10B 93.6%, 59.6 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 Exp $0.41 against Qwen3.5-122B-A10B $2.08 per million output tokens, 5.1x apart.
Context window
DeepSeek V3.2 Exp takes 164K tokens, Qwen3.5-122B-A10B 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 ExpBarsQwen3.5-122B-A10BTies
Coding221 tie
Intelligence01
Agentic work01
Reasoning23
Math11
Knowledge22
General156
All shared boards22161 tie
CodingLike-for-likeFour of these boards feed the Vibe Coding Index22
Coding benchmarks for DeepSeek V3.2 Exp and Qwen3.5-122B-A10B
BenchmarkDeepSeek V3.2 ExpQwen3.5-122B-A10BLeader
Aider polyglot74.2%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena WebDev12721361Qwen3.5-122B-A10B
AA Coding IndexNot measured43.3Only Qwen3.5-122B-A10B measured
LiveCodeBench (Artificial Analysis run)78.9%Not measuredOnly DeepSeek V3.2 Exp measured
SciCodeNot measured39.7%Only Qwen3.5-122B-A10B measured
Terminal-Bench Hard (Artificial Analysis run)31.1%31.1%Tie
WeirdML39.5%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: coding14381436DeepSeek V3.2 Exp
LMArena Text: software and IT14381436DeepSeek V3.2 Exp
LMArena WebDev: ReactNot measured1353Only Qwen3.5-122B-A10B measured
LMArena WebDev: HTML12811351Qwen3.5-122B-A10B
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for DeepSeek V3.2 Exp and Qwen3.5-122B-A10B
BenchmarkDeepSeek V3.2 ExpQwen3.5-122B-A10BLeader
AA Intelligence Index16.617.7Qwen3.5-122B-A10B
Epoch Capabilities Index144.9Not measuredOnly DeepSeek V3.2 Exp measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for DeepSeek V3.2 Exp and Qwen3.5-122B-A10B
BenchmarkDeepSeek V3.2 ExpQwen3.5-122B-A10BLeader
τ²-Bench Telecom33.9%93.6%Qwen3.5-122B-A10B
TheAgentCompany42.9%Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index23
Reasoning benchmarks for DeepSeek V3.2 Exp and Qwen3.5-122B-A10B
BenchmarkDeepSeek V3.2 ExpQwen3.5-122B-A10BLeader
GPQA Diamond (Artificial Analysis run)79.7%85.7%Qwen3.5-122B-A10B
Humanity's Last Exam (Artificial Analysis run)14.9%25.2%Qwen3.5-122B-A10B
Mystery game puzzlesNot measured17.0%Only Qwen3.5-122B-A10B measured
LMArena Text: hard prompts14291421DeepSeek V3.2 Exp
LMArena Text: expert14221431Qwen3.5-122B-A10B
LMArena Text: hard prompts in English14441431DeepSeek V3.2 Exp
LMArena Vision: diagramsNot measured1249Only Qwen3.5-122B-A10B measured
LMArena Vision: homeworkNot measured1261Only Qwen3.5-122B-A10B measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index11
Math benchmarks for DeepSeek V3.2 Exp and Qwen3.5-122B-A10B
BenchmarkDeepSeek V3.2 ExpQwen3.5-122B-A10BLeader
AA Math Index87.7Not measuredOnly DeepSeek V3.2 Exp measured
AIME 2025 (Artificial Analysis run)87.7%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: math14221431Qwen3.5-122B-A10B
LMArena Text: mathematical work14331431DeepSeek V3.2 Exp
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
Knowledge benchmarks for DeepSeek V3.2 Exp and Qwen3.5-122B-A10B
BenchmarkDeepSeek V3.2 ExpQwen3.5-122B-A10BLeader
MMLU Pro (Artificial Analysis run)85.0%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: science14431432DeepSeek V3.2 Exp
LMArena Text: medicine and healthcare14681423DeepSeek V3.2 Exp
LMArena Text: legal and government14191422Qwen3.5-122B-A10B
LMArena Text: business and finance14121414Qwen3.5-122B-A10B
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for DeepSeek V3.2 Exp and Qwen3.5-122B-A10B
BenchmarkDeepSeek V3.2 ExpQwen3.5-122B-A10BLeader
Design Arena: websites1179Not measuredOnly DeepSeek V3.2 Exp measured
Design Arena: UI components1166Not measuredOnly DeepSeek V3.2 Exp measured
Design Arena: game dev1145Not measuredOnly DeepSeek V3.2 Exp measured
Design Arena: data viz1152Not measuredOnly DeepSeek V3.2 Exp measured
Design Arena: 3D1148Not measuredOnly DeepSeek V3.2 Exp measured
Design Arena: all code categories1171Not measuredOnly DeepSeek V3.2 Exp measured
Design Arena: SVG1031Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index156
General benchmarks for DeepSeek V3.2 Exp and Qwen3.5-122B-A10B
BenchmarkDeepSeek V3.2 ExpQwen3.5-122B-A10BLeader
IFBench54.1%75.7%Qwen3.5-122B-A10B
Long context reasoning (AA-LCR)72.3%76.3%Qwen3.5-122B-A10B
DTBench87.7%84.3%DeepSeek V3.2 Exp
LMCA29.1%32.2%Qwen3.5-122B-A10B
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 Text14251417DeepSeek V3.2 Exp
LMArena Text: instruction following14011399DeepSeek V3.2 Exp
LMArena Text: creative writing14041368DeepSeek V3.2 Exp
LMArena VisionNot measured1244Only Qwen3.5-122B-A10B measured
LMArena Text: English14411428DeepSeek V3.2 Exp
LMArena Text: non-English14041401DeepSeek V3.2 Exp
LMArena Text: Chinese14611463Qwen3.5-122B-A10B
LMArena Text: German14401425DeepSeek V3.2 Exp
LMArena Text: Japanese13311367Qwen3.5-122B-A10B
LMArena Text: Korean13721353DeepSeek V3.2 Exp
LMArena Text: French14341443Qwen3.5-122B-A10B
LMArena Text: Spanish14411425DeepSeek V3.2 Exp
LMArena Text: Russian14121400DeepSeek V3.2 Exp
LMArena Text: Polish14351398DeepSeek V3.2 Exp
LMArena Text: multi-turn14221416DeepSeek V3.2 Exp
LMArena Text: longer queries14181410DeepSeek V3.2 Exp
LMArena Text: writing and language14071387DeepSeek V3.2 Exp
LMArena Text: entertainment and media14071366DeepSeek V3.2 Exp
LMArena Vision: EnglishNot measured1249Only Qwen3.5-122B-A10B measured
LMArena Vision: ChineseNot measured1301Only Qwen3.5-122B-A10B measured
LMArena Vision: reading textNot measured1251Only Qwen3.5-122B-A10B measured
LMArena Vision: humorNot measured1243Only Qwen3.5-122B-A10B measured
LMArena Vision: creative writingNot measured1220Only Qwen3.5-122B-A10B measured
Neither model has a result on the other 16 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 Qwen3.5-122B-A10B
BenchmarkDeepSeek V3.2 ExpQwen3.5-122B-A10BLeader
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
Qwen3.5-122B-A10B$0.0013Fits 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
Qwen3.5-122B-A10B$0.019Fits 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
Qwen3.5-122B-A10B$0.073Fits 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 Qwen3.5-122B-A10B
SpecificationDeepSeek V3.2 ExpQwen3.5-122B-A10B
MakerDeepSeekQwen
WeightsOpen weightsOpen weights
ReleasedSeptember 29, 2025February 25, 2026
Context window164K262K
Input $/Mtok$0.27$0.26
Output $/Mtok$0.41$2.08
Coding index55.022.9
Independent measurements behind it21
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 Exp better than Qwen3.5-122B-A10B for coding?

Pick DeepSeek V3.2 Exp for coding: it scores 55.0 on the Vibe Coding Index against 22.9 for Qwen3.5-122B-A10B. Pick Qwen3.5-122B-A10B when the context window is larger, 262K against 164K tokens, or when what matters is LMArena WebDev or LMArena WebDev: HTML, where it leads.

Which is cheaper, DeepSeek V3.2 Exp or Qwen3.5-122B-A10B?

DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 per million output tokens; Qwen3.5-122B-A10B costs $0.26 and $2.08. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V3.2 Exp or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B, with 262K tokens against 164K.

How many benchmarks is the DeepSeek V3.2 Exp vs Qwen3.5-122B-A10B comparison based on?

39 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 Qwen3.5-122B-A10B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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