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DeepSeek V3.2 vs Qwen3 235B A22B Thinking 2507

DeepSeek V3.2 leads Qwen3 235B A22B Thinking 2507 on the Artificial Analysis Intelligence Index, 21.5 to 12.7, and DeepSeek V3.2 costs 4.0x less per output token ($0.88 vs $3.50 per million). Updated October 22, 2026; 38 benchmarks have a result for both.

Replace DeepSeek V3.2 Replace Qwen3 235B A22B Thinking 2507
DeepSeek V3.2DeepSeek
Coding
30.0
Overall
37.9
Output $/M
$0.88
31
Qwen3 235B A22B Thinking 2507Qwen
Coding
No data
Overall
52.9
Output $/M
$3.50
7
vs boards won of 38 shared

DeepSeek V3.2 or Qwen3 235B A22B Thinking 2507: which to pick

Only DeepSeek V3.2 has a coding score, 30.0 on the Vibe Coding Index; Qwen3 235B A22B Thinking 2507 has none, so the two cannot be ranked on coding.

Pick Qwen3 235B A22B Thinking 2507 for work measured by LMArena Text: expert or LMArena Text: medicine and healthcare, where it leads.

Model ADeepSeek V3.2DeepSeek30.0/1003 independent benchmarks$0.99 per solved taskModel BQwen3 235B A22B Thinking 2507QwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
38
DeepSeek V3.2 only
37
Qwen3 235B A22B Thinking 2507 only
8
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 30.0 from 3 benchmarks, Qwen3 235B A22B Thinking 2507 not benchmarked.
Widest category
Web design, 20.3 points apart on average over 6 shared benchmarks.
Widest single gap
Design Arena: data viz: DeepSeek V3.2 1158 against Qwen3 235B A22B Thinking 2507 950, 26.0 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 $0.88 against Qwen3 235B A22B Thinking 2507 $3.50 per million output tokens, 4.0x apart.
Context window
DeepSeek V3.2 takes 164K tokens, Qwen3 235B A22B Thinking 2507 128K.

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 V3.2BarsQwen3 235B A22B Thinking 2507Ties
Coding30
Intelligence10
Agentic work10
Reasoning21
Math20
Knowledge22
Web design60
General144
All shared boards317
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for DeepSeek V3.2 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V3.2Qwen3 235B A22B Thinking 2507Leader
SWE-bench Verified70.0%Not measuredOnly DeepSeek V3.2 measured
SWE-bench Multilingual59.0%Not measuredOnly DeepSeek V3.2 measured
LMArena WebDev1362Not measuredOnly DeepSeek V3.2 measured
AA Coding Index44.222.1DeepSeek V3.2
LiveCodeBench (Vals AI)80.7%Not measuredOnly DeepSeek V3.2 measured
SWE-bench Verified (Vals AI)67.6%Not measuredOnly DeepSeek V3.2 measured
Vibe Code Bench (Vals AI)5.1%Not measuredOnly DeepSeek V3.2 measured
LiveCodeBench (Artificial Analysis run)86.2%Not measuredOnly DeepSeek V3.2 measured
Terminal-Bench Hard (Artificial Analysis run)35.6%Not measuredOnly DeepSeek V3.2 measured
Terminal-Bench39.6%Not measuredOnly DeepSeek V3.2 measured
WeirdMLNot measured41.0%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: coding14531424DeepSeek V3.2
LMArena Text: software and IT14491431DeepSeek V3.2
LMArena WebDev: React1350Not measuredOnly DeepSeek V3.2 measured
LMArena WebDev: HTML1371Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V3.2 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V3.2Qwen3 235B A22B Thinking 2507Leader
AA Intelligence Index21.512.7DeepSeek V3.2
Epoch Capabilities Index146.1Not measuredOnly DeepSeek V3.2 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for DeepSeek V3.2 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V3.2Qwen3 235B A22B Thinking 2507Leader
AA Agentic IndexNot measured1.3Only Qwen3 235B A22B Thinking 2507 measured
τ²-Bench Telecom90.6%Not measuredOnly DeepSeek V3.2 measured
APEX-Agents21.3%Not measuredOnly DeepSeek V3.2 measured
Vending-Bench 2$1,034-$11DeepSeek V3.2
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
Reasoning benchmarks for DeepSeek V3.2 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V3.2Qwen3 235B A22B Thinking 2507Leader
GPQA Diamond80.3%Not measuredOnly DeepSeek V3.2 measured
GPQA Diamond (Artificial Analysis run)84.0%Not measuredOnly DeepSeek V3.2 measured
Humanity's Last Exam (Artificial Analysis run)24.6%Not measuredOnly DeepSeek V3.2 measured
GPQA Diamond (Epoch AI run)Not measured80.1%Only Qwen3 235B A22B Thinking 2507 measured
ARC-AGI57.0%Not measuredOnly DeepSeek V3.2 measured
ARC-AGI-24.0%Not measuredOnly DeepSeek V3.2 measured
Mystery game puzzlesNot measured9.0%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: hard prompts14341416DeepSeek V3.2
LMArena Text: expert14361463Qwen3 235B A22B Thinking 2507
LMArena Text: hard prompts in English14461432DeepSeek V3.2
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V3.2 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V3.2Qwen3 235B A22B Thinking 2507Leader
AIME84.6%Not measuredOnly DeepSeek V3.2 measured
MGSM (Vals AI)86.0%Not measuredOnly DeepSeek V3.2 measured
AA Math Index92.0Not measuredOnly DeepSeek V3.2 measured
AIME 2025 (Artificial Analysis run)92.0%Not measuredOnly DeepSeek V3.2 measured
OTIS Mock AIMENot measured86.7%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: math14351412DeepSeek V3.2
LMArena Text: mathematical work14401435DeepSeek V3.2
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
Knowledge benchmarks for DeepSeek V3.2 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V3.2Qwen3 235B A22B Thinking 2507Leader
MMLU Pro84.9%Not measuredOnly DeepSeek V3.2 measured
LegalBench (Vals AI)76.1%Not measuredOnly DeepSeek V3.2 measured
CaseLaw (Vals AI)55.4%Not measuredOnly DeepSeek V3.2 measured
CorpFin (Vals AI)51.0%Not measuredOnly DeepSeek V3.2 measured
TaxEval (Vals AI)68.2%Not measuredOnly DeepSeek V3.2 measured
MedQA (Vals AI)93.9%Not measuredOnly DeepSeek V3.2 measured
MMLU Pro (Artificial Analysis run)86.2%Not measuredOnly DeepSeek V3.2 measured
SimpleQA VerifiedNot measured40.4%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: science14461433DeepSeek V3.2
LMArena Text: medicine and healthcare14401456Qwen3 235B A22B Thinking 2507
LMArena Text: legal and government14251415DeepSeek V3.2
LMArena Text: business and finance14101413Qwen3 235B A22B Thinking 2507
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for DeepSeek V3.2 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V3.2Qwen3 235B A22B Thinking 2507Leader
Design Arena: websites11751052DeepSeek V3.2
Design Arena: UI components1146942DeepSeek V3.2
Design Arena: game dev1131956DeepSeek V3.2
Design Arena: data viz1158950DeepSeek V3.2
Design Arena: 3D1132997DeepSeek V3.2
Design Arena: all code categories11631032DeepSeek V3.2
Design Arena: SVG1032Not measuredOnly DeepSeek V3.2 measured
Design Arena: ASCII art1083Not measuredOnly 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 index144
General benchmarks for DeepSeek V3.2 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V3.2Qwen3 235B A22B Thinking 2507Leader
IFBench60.7%Not measuredOnly DeepSeek V3.2 measured
Long context reasoning (AA-LCR)73.3%Not measuredOnly DeepSeek V3.2 measured
DTBench85.6%80.3%DeepSeek V3.2
LMCA28.8%29.3%Qwen3 235B A22B Thinking 2507
Fiction.LiveBenchNot measured75.0%Only Qwen3 235B A22B Thinking 2507 measured
Creative writing (Lech Mazur)Not measured82.4%Only Qwen3 235B A22B Thinking 2507 measured
CL-bench12.4%Not measuredOnly DeepSeek V3.2 measured
CL-bench Life7.4%Not measuredOnly DeepSeek V3.2 measured
LMArena Text14251415DeepSeek V3.2
LMArena Text: instruction following14131386DeepSeek V3.2
LMArena Text: creative writing14001384DeepSeek V3.2
LMArena Text: English14391429DeepSeek V3.2
LMArena Text: non-English14091397DeepSeek V3.2
LMArena Text: Chinese14551481Qwen3 235B A22B Thinking 2507
LMArena Text: German14131408DeepSeek V3.2
LMArena Text: Japanese13741386Qwen3 235B A22B Thinking 2507
LMArena Text: Korean13701375Qwen3 235B A22B Thinking 2507
LMArena Text: French1429Not measuredOnly DeepSeek V3.2 measured
LMArena Text: Spanish14241389DeepSeek V3.2
LMArena Text: Russian14241401DeepSeek V3.2
LMArena Text: Polish14191390DeepSeek V3.2
LMArena Text: multi-turn14271406DeepSeek V3.2
LMArena Text: longer queries14281400DeepSeek V3.2
LMArena Text: writing and language14071388DeepSeek V3.2
LMArena Text: entertainment and media13951370DeepSeek V3.2
Neither model has a result on the other 21 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.2 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V3.2Qwen3 235B A22B Thinking 2507Leader
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$0.0007Fits in one request
Qwen3 235B A22B Thinking 2507$0.0022Fits in one request

DeepSeek V3.2 costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2$0.017Fits in one request
Qwen3 235B A22B Thinking 2507$0.033Fits in one request

DeepSeek V3.2 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2$0.067Exceeds the context window
Qwen3 235B A22B Thinking 2507$0.125Exceeds 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 V3.2 and Qwen3 235B A22B Thinking 2507
SpecificationDeepSeek V3.2Qwen3 235B A22B Thinking 2507
MakerDeepSeekQwen
WeightsOpen weightsOpen weights
ReleasedDecember 1, 2025July 25, 2025
Context window164K128K
Input $/Mtok$0.29$0.45
Output $/Mtok$0.88$3.50
Coding index30.0Not benchmarked
Independent measurements behind it30
Cost per solved task$0.99Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 better than Qwen3 235B A22B Thinking 2507 for coding?

Only DeepSeek V3.2 has a coding score, 30.0 on the Vibe Coding Index; Qwen3 235B A22B Thinking 2507 has none, so the two cannot be ranked on coding. Pick Qwen3 235B A22B Thinking 2507 for work measured by LMArena Text: expert or LMArena Text: medicine and healthcare, where it leads.

Which is cheaper, DeepSeek V3.2 or Qwen3 235B A22B Thinking 2507?

DeepSeek V3.2 costs $0.29 per million input tokens and $0.88 per million output tokens; Qwen3 235B A22B Thinking 2507 costs $0.45 and $3.50. Cost per solved task is known for DeepSeek V3.2 only.

Which has the bigger context window, DeepSeek V3.2 or Qwen3 235B A22B Thinking 2507?

DeepSeek V3.2, with 164K tokens against 128K.

How many benchmarks is the DeepSeek V3.2 vs Qwen3 235B A22B Thinking 2507 comparison based on?

38 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.2's coding index rests on 3 independent benchmarks and Qwen3 235B A22B Thinking 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.

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