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DeepSeek V3.2 Exp vs Qwen3.5 Plus 2026-04-20

DeepSeek V3.2 Exp costs 4.4x less per output token than Qwen3.5 Plus 2026-04-20 ($0.41 vs $1.80 per million). Updated October 22, 2026; 5 benchmarks have a result for both.

DeepSeek V3.2 ExpDeepSeek
Coding
No data
Overall
No data
Output $/M
$0.41
1
Qwen3.5 Plus 2026-04-20Qwen
Coding
39.5
Overall
No data
Output $/M
$1.80
4
vs boards won of 5 shared

DeepSeek V3.2 Exp or Qwen3.5 Plus 2026-04-20: which to pick

Only Qwen3.5 Plus 2026-04-20 has a coding score, 39.5 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 4.4x cheaper ($0.41 vs $1.80 per million) and work measured by DTBench, where it leads.

Shared results
5
DeepSeek V3.2 Exp only
54
Qwen3.5 Plus 2026-04-20 only
20
Like-for-like categories
2 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, Qwen3.5 Plus 2026-04-20 39.5 from 2 benchmarks.
Widest category
General, 6.0 points apart on average over 4 shared benchmarks.
Widest single gap
LMCA: DeepSeek V3.2 Exp 29.1% against Qwen3.5 Plus 2026-04-20 36.4%, 7.2 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 Exp $0.41 against Qwen3.5 Plus 2026-04-20 $1.80 per million output tokens, 4.4x apart.
Context window
DeepSeek V3.2 Exp takes 164K tokens, Qwen3.5 Plus 2026-04-20 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 ExpBarsQwen3.5 Plus 2026-04-20Ties
Intelligence01
General13
All shared boards14
CodingDirectional onlySix of these boards feed the Vibe Coding Index12 boards, none shared
Coding benchmarks for DeepSeek V3.2 Exp and Qwen3.5 Plus 2026-04-20
BenchmarkDeepSeek V3.2 ExpQwen3.5 Plus 2026-04-20Leader
Aider polyglot74.2%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena WebDev1272Not measuredOnly DeepSeek V3.2 Exp measured
LiveCodeBench (Vals AI)Not measured85.3%Only Qwen3.5 Plus 2026-04-20 measured
SWE-bench Verified (Vals AI)Not measured71.2%Only Qwen3.5 Plus 2026-04-20 measured
Vibe Code Bench (Vals AI)Not measured15.7%Only Qwen3.5 Plus 2026-04-20 measured
LiveCodeBench (Artificial Analysis run)78.9%Not measuredOnly DeepSeek V3.2 Exp measured
Terminal-Bench Hard (Artificial Analysis run)31.1%Not measuredOnly DeepSeek V3.2 Exp measured
WeirdML39.5%Not measuredOnly DeepSeek V3.2 Exp measured
ALE-BenchNot measured608.9Only Qwen3.5 Plus 2026-04-20 measured
LMArena Text: coding1438Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: software and IT1438Not measuredOnly DeepSeek V3.2 Exp measured
LMArena WebDev: HTML1281Not measuredOnly DeepSeek V3.2 Exp measured
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 Plus 2026-04-20
BenchmarkDeepSeek V3.2 ExpQwen3.5 Plus 2026-04-20Leader
AA Intelligence Index16.6Not measuredOnly DeepSeek V3.2 Exp measured
Epoch Capabilities Index144.9146.2Qwen3.5 Plus 2026-04-20
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Agentic work benchmarks for DeepSeek V3.2 Exp and Qwen3.5 Plus 2026-04-20
BenchmarkDeepSeek V3.2 ExpQwen3.5 Plus 2026-04-20Leader
τ²-Bench Telecom33.9%Not measuredOnly DeepSeek V3.2 Exp measured
TheAgentCompany42.9%Not measuredOnly DeepSeek V3.2 Exp measured
Vending-Bench 2Not measured$1Only Qwen3.5 Plus 2026-04-20 measured
Berkeley Function Calling Leaderboard (BFCL)56.7%Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 37 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
Reasoning benchmarks for DeepSeek V3.2 Exp and Qwen3.5 Plus 2026-04-20
BenchmarkDeepSeek V3.2 ExpQwen3.5 Plus 2026-04-20Leader
GPQA DiamondNot measured87.4%Only Qwen3.5 Plus 2026-04-20 measured
MMMU Pro (Vals AI)Not measured22.8%Only Qwen3.5 Plus 2026-04-20 measured
GPQA Diamond (Artificial Analysis run)79.7%Not measuredOnly DeepSeek V3.2 Exp measured
Humanity's Last Exam (Artificial Analysis run)14.9%Not measuredOnly DeepSeek V3.2 Exp measured
GPQA Diamond (Epoch AI run)Not measured84.8%Only Qwen3.5 Plus 2026-04-20 measured
Chess puzzlesNot measured8.0%Only Qwen3.5 Plus 2026-04-20 measured
Mystery game puzzlesNot measured17.0%Only Qwen3.5 Plus 2026-04-20 measured
LMArena Text: hard prompts1429Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: expert1422Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: hard prompts in English1444Not measuredOnly DeepSeek V3.2 Exp measured
Kagi LLM Benchmark52.2%Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 11 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Math benchmarks for DeepSeek V3.2 Exp and Qwen3.5 Plus 2026-04-20
BenchmarkDeepSeek V3.2 ExpQwen3.5 Plus 2026-04-20Leader
AIMENot measured86.0%Only Qwen3.5 Plus 2026-04-20 measured
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 measured86.7%Only Qwen3.5 Plus 2026-04-20 measured
LMArena Text: math1422Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: mathematical work1433Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
Knowledge benchmarks for DeepSeek V3.2 Exp and Qwen3.5 Plus 2026-04-20
BenchmarkDeepSeek V3.2 ExpQwen3.5 Plus 2026-04-20Leader
MMLU ProNot measured87.2%Only Qwen3.5 Plus 2026-04-20 measured
LegalBench (Vals AI)Not measured85.1%Only Qwen3.5 Plus 2026-04-20 measured
CaseLaw (Vals AI)Not measured59.7%Only Qwen3.5 Plus 2026-04-20 measured
CorpFin (Vals AI)Not measured65.3%Only Qwen3.5 Plus 2026-04-20 measured
MortgageTax (Vals AI)Not measured60.8%Only Qwen3.5 Plus 2026-04-20 measured
MedQA (Vals AI)Not measured95.2%Only Qwen3.5 Plus 2026-04-20 measured
MMLU Pro (Artificial Analysis run)85.0%Not measuredOnly DeepSeek V3.2 Exp measured
SimpleQA VerifiedNot measured25.4%Only Qwen3.5 Plus 2026-04-20 measured
LMArena Text: science1443Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: medicine and healthcare1468Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: legal and government1419Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: business and finance1412Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 6 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 Plus 2026-04-20
BenchmarkDeepSeek V3.2 ExpQwen3.5 Plus 2026-04-20Leader
Design Arena: websites1178Not measuredOnly DeepSeek V3.2 Exp measured
Design Arena: UI components1164Not measuredOnly DeepSeek V3.2 Exp measured
Design Arena: game dev1144Not 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 categories1170Not 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 index13
General benchmarks for DeepSeek V3.2 Exp and Qwen3.5 Plus 2026-04-20
BenchmarkDeepSeek V3.2 ExpQwen3.5 Plus 2026-04-20Leader
SAGE (Vals AI)Not measured30.4%Only Qwen3.5 Plus 2026-04-20 measured
IFBench54.1%Not measuredOnly DeepSeek V3.2 Exp measured
Long context reasoning (AA-LCR)72.3%Not measuredOnly DeepSeek V3.2 Exp measured
DTBench87.7%80.5%DeepSeek V3.2 Exp
LMCA29.1%36.4%Qwen3.5 Plus 2026-04-20
Fiction.LiveBench83.3%Not measuredOnly DeepSeek V3.2 Exp measured
CL-bench13.2%19.8%Qwen3.5 Plus 2026-04-20
CL-bench Life9.5%12.4%Qwen3.5 Plus 2026-04-20
LMArena Text1425Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: instruction following1401Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: creative writing1404Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: English1441Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: non-English1404Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Chinese1461Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: German1440Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Japanese1331Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Korean1372Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: French1434Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Spanish1441Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Russian1412Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Polish1435Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: multi-turn1422Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: longer queries1418Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: writing and language1407Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: entertainment and media1407Not measuredOnly DeepSeek V3.2 Exp measured
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 Exp and Qwen3.5 Plus 2026-04-20
BenchmarkDeepSeek V3.2 ExpQwen3.5 Plus 2026-04-20Leader
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 Plus 2026-04-20$0.0012Fits 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 Plus 2026-04-20$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
Qwen3.5 Plus 2026-04-20$0.078Fits 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 Plus 2026-04-20
SpecificationDeepSeek V3.2 ExpQwen3.5 Plus 2026-04-20
MakerDeepSeekQwen
WeightsOpen weightsNo public weights listed
ReleasedSeptember 29, 2025April 27, 2026
Context window164K1M
Input $/Mtok$0.27$0.30
Output $/Mtok$0.41$1.80
Coding indexNot benchmarked39.5
Independent measurements behind it12
Cost per solved taskNot computable$1.35
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 Exp better than Qwen3.5 Plus 2026-04-20 for coding?

Only Qwen3.5 Plus 2026-04-20 has a coding score, 39.5 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 4.4x cheaper ($0.41 vs $1.80 per million) and work measured by DTBench, where it leads.

Which is cheaper, DeepSeek V3.2 Exp or Qwen3.5 Plus 2026-04-20?

DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 per million output tokens; Qwen3.5 Plus 2026-04-20 costs $0.30 and $1.80. Cost per solved task is known for Qwen3.5 Plus 2026-04-20 only.

Which has the bigger context window, DeepSeek V3.2 Exp or Qwen3.5 Plus 2026-04-20?

Qwen3.5 Plus 2026-04-20, with 1M tokens against 164K.

How many benchmarks is the DeepSeek V3.2 Exp vs Qwen3.5 Plus 2026-04-20 comparison based on?

5 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.2 Exp's coding index rests on 1 independent benchmark and Qwen3.5 Plus 2026-04-20's on 2. Where only one model has a result, the page says so instead of naming a winner.

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