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DeepSeek V4.1 Flash 1017 vs Qwen3 32B

DeepSeek V4.1 Flash 1017 leads Qwen3 32B on the Artificial Analysis Intelligence Index, 39.5 to 7.3, and Qwen3 32B costs 1.5x less per output token ($0.40 vs $0.60 per million). Updated October 22, 2026; 6 benchmarks have a result for both.

DeepSeek V4.1 Flash 1017DeepSeek
Coding
70.3
Overall
67.6
Output $/M
$0.60
6
Qwen3 32BQwen
Coding
No data
Overall
40.8
Output $/M
$0.40
0
vs boards won of 6 shared

DeepSeek V4.1 Flash 1017 or Qwen3 32B: which to pick

Only DeepSeek V4.1 Flash 1017 has a coding score, 70.3 on the Vibe Coding Index; Qwen3 32B has none, so the two cannot be ranked on coding.

Pick Qwen3 32B for output tokens 1.5x cheaper ($0.40 vs $0.60 per million).

Shared results
6
DeepSeek V4.1 Flash 1017 only
33
Qwen3 32B only
39
Like-for-like categories
5 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 V4.1 Flash 1017 70.3 from 4 benchmarks, Qwen3 32B not benchmarked.
Widest category
General, 82.7 points apart on average over 1 shared benchmark.
Widest single gap
Long context reasoning (AA-LCR): DeepSeek V4.1 Flash 1017 82.7% against Qwen3 32B 0.0%, 82.7 points apart on a 0 to 100 scale.
Output price
DeepSeek V4.1 Flash 1017 $0.60 against Qwen3 32B $0.40 per million output tokens, 1.5x apart.
Context window
DeepSeek V4.1 Flash 1017 takes 1.05M tokens, Qwen3 32B 131K.

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 V4.1 Flash 1017BarsQwen3 32BTies
Coding10
Intelligence10
Reasoning20
Math10
General10
All shared boards60
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for DeepSeek V4.1 Flash 1017 and Qwen3 32B
BenchmarkDeepSeek V4.1 Flash 1017Qwen3 32BLeader
Aider polyglotNot measured40.0%Only Qwen3 32B measured
LiveBench coding96.0%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LMArena WebDev1664Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Terminal-Bench 4 (Vals AI)31.8%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Vibe Code Bench (Vals AI)87.7%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Code migration (Vals AI)44.2%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveCodeBench (Artificial Analysis run)Not measured54.6%Only Qwen3 32B measured
SciCode55.9%36.0%DeepSeek V4.1 Flash 1017
Terminal-Bench Hard (Artificial Analysis run)Not measured3.0%Only Qwen3 32B measured
ALE-Bench1622.0Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LMArena Text: codingNot measured1357Only Qwen3 32B measured
LMArena Text: software and ITNot measured1366Only Qwen3 32B measured
LMArena WebDev: React1667Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LMArena WebDev: HTML1687Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4.1 Flash 1017 and Qwen3 32B
BenchmarkDeepSeek V4.1 Flash 1017Qwen3 32BLeader
AA Intelligence Index39.57.3DeepSeek V4.1 Flash 1017
Epoch Capabilities IndexNot measured138.4Only Qwen3 32B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
Agentic work benchmarks for DeepSeek V4.1 Flash 1017 and Qwen3 32B
BenchmarkDeepSeek V4.1 Flash 1017Qwen3 32BLeader
Design Arena: spreadsheets1245Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench research79.5%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench browser76.0%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench long agentic50.9%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Finance Agent (Vals AI)57.0%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Tax Agent Bench (Vals AI)44.4%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Legal Research Bench (Vals AI)45.2%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Harvey's Legal Agent Benchmark (Vals AI)14.2%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Excel Modeling Benchmark (Vals AI)61.8%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
τ²-Bench TelecomNot measured29.8%Only Qwen3 32B measured
Berkeley Function Calling Leaderboard (BFCL)Not measured48.7%Only Qwen3 32B measured
BrowseComp-PlusNot measured10.7%Only Qwen3 32B measured
Neither model has a result on the other 29 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for DeepSeek V4.1 Flash 1017 and Qwen3 32B
BenchmarkDeepSeek V4.1 Flash 1017Qwen3 32BLeader
LiveBench reasoning89.1%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
GPQA Diamond (Artificial Analysis run)Not measured66.8%Only Qwen3 32B measured
Humanity's Last Exam (Artificial Analysis run)43.3%7.4%DeepSeek V4.1 Flash 1017
GPQA Diamond (Epoch AI run)93.2%65.7%DeepSeek V4.1 Flash 1017
Chess puzzles46.0%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Mystery game puzzles49.0%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LMArena Text: hard promptsNot measured1334Only Qwen3 32B measured
LMArena Text: expertNot measured1362Only Qwen3 32B measured
LMArena Text: hard prompts in EnglishNot measured1350Only Qwen3 32B measured
Kagi LLM BenchmarkNot measured48.7%Only Qwen3 32B measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index10
Math benchmarks for DeepSeek V4.1 Flash 1017 and Qwen3 32B
BenchmarkDeepSeek V4.1 Flash 1017Qwen3 32BLeader
AA Math IndexNot measured73.0Only Qwen3 32B measured
AIME 2025 (Artificial Analysis run)Not measured73.0%Only Qwen3 32B measured
OTIS Mock AIME99.4%66.9%DeepSeek V4.1 Flash 1017
FrontierMath, tiers 1 to 371.2%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
FrontierMath, tier 446.3%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LMArena Text: mathNot measured1399Only Qwen3 32B measured
LMArena Text: mathematical workNot measured1420Only Qwen3 32B measured
Neither model has a result on the other 6 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Knowledge benchmarks for DeepSeek V4.1 Flash 1017 and Qwen3 32B
BenchmarkDeepSeek V4.1 Flash 1017Qwen3 32BLeader
MMLU Pro (Artificial Analysis run)Not measured79.8%Only Qwen3 32B measured
SimpleQA Verified42.5%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LMArena Text: scienceNot measured1372Only Qwen3 32B measured
LMArena Text: medicine and healthcareNot measured1368Only Qwen3 32B measured
LMArena Text: legal and governmentNot measured1324Only Qwen3 32B measured
LMArena Text: business and financeNot measured1318Only Qwen3 32B measured
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for DeepSeek V4.1 Flash 1017 and Qwen3 32B
BenchmarkDeepSeek V4.1 Flash 1017Qwen3 32BLeader
Design Arena: websites1311Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Design Arena: UI components1303Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Design Arena: game dev1357Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Design Arena: data viz1330Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Design Arena: 3D1358Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Design Arena: all code categories1332Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Design Arena: ASCII art1242Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench design83.4%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
General benchmarks for DeepSeek V4.1 Flash 1017 and Qwen3 32B
BenchmarkDeepSeek V4.1 Flash 1017Qwen3 32BLeader
Vals Index61.3%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench data analysis79.5%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
IFBenchNot measured36.3%Only Qwen3 32B measured
Long context reasoning (AA-LCR)82.7%0.0%DeepSeek V4.1 Flash 1017
DTBenchNot measured67.5%Only Qwen3 32B measured
LMCANot measured17.3%Only Qwen3 32B measured
Fiction.LiveBenchNot measured74.2%Only Qwen3 32B measured
LMArena TextNot measured1340Only Qwen3 32B measured
LMArena Text: instruction followingNot measured1305Only Qwen3 32B measured
LMArena Text: creative writingNot measured1297Only Qwen3 32B measured
LMArena Text: EnglishNot measured1359Only Qwen3 32B measured
LMArena Text: non-EnglishNot measured1317Only Qwen3 32B measured
LMArena Text: ChineseNot measured1357Only Qwen3 32B measured
LMArena Text: GermanNot measured1341Only Qwen3 32B measured
LMArena Text: RussianNot measured1311Only Qwen3 32B measured
LMArena Text: multi-turnNot measured1331Only Qwen3 32B measured
LMArena Text: longer queriesNot measured1327Only Qwen3 32B measured
LMArena Text: writing and languageNot measured1298Only Qwen3 32B measured
LMArena Text: entertainment and mediaNot measured1279Only Qwen3 32B measured
Neither model has a result on the other 27 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4.1 Flash 1017 and Qwen3 32B
BenchmarkDeepSeek V4.1 Flash 1017Qwen3 32BLeader
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 V4.1 Flash 1017$0.0004Fits in one request
Qwen3 32B$0.0003Fits in one request

Qwen3 32B costs less

Repository review

50K input + 3K output tokens

DeepSeek V4.1 Flash 1017$0.0093Fits in one request
Qwen3 32B$0.0082Fits in one request

Qwen3 32B costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4.1 Flash 1017$0.036Fits in one request
Qwen3 32B$0.032Exceeds the context window

Qwen3 32B 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 V4.1 Flash 1017 and Qwen3 32B
SpecificationDeepSeek V4.1 Flash 1017Qwen3 32B
MakerDeepSeekQwen
WeightsOpen weightsOpen weights
ReleasedOctober 17, 2026April 28, 2025
Context window1.05M131K
Input $/Mtok$0.15$0.14
Output $/Mtok$0.60$0.40
Coding index70.3Not benchmarked
Independent measurements behind it40
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4.1 Flash 1017 better than Qwen3 32B for coding?

Only DeepSeek V4.1 Flash 1017 has a coding score, 70.3 on the Vibe Coding Index; Qwen3 32B has none, so the two cannot be ranked on coding. Pick Qwen3 32B for output tokens 1.5x cheaper ($0.40 vs $0.60 per million).

Which is cheaper, DeepSeek V4.1 Flash 1017 or Qwen3 32B?

DeepSeek V4.1 Flash 1017 costs $0.15 per million input tokens and $0.60 per million output tokens; Qwen3 32B costs $0.14 and $0.40. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V4.1 Flash 1017 or Qwen3 32B?

DeepSeek V4.1 Flash 1017, with 1.05M tokens against 131K.

How many benchmarks is the DeepSeek V4.1 Flash 1017 vs Qwen3 32B comparison based on?

6 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4.1 Flash 1017's coding index rests on 4 independent benchmarks and Qwen3 32B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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