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DeepSeek V4 Pro 0423 vs Qwen3.5-35B-A3B

DeepSeek V4 Pro 0423 leads Qwen3.5-35B-A3B on the Artificial Analysis Intelligence Index, 30.4 to 19.3, and Qwen3.5-35B-A3B costs 2.3x less per output token ($1.30 vs $2.976 per million). Updated October 22, 2026; 39 benchmarks have a result for both.

Replace DeepSeek V4 Pro 0423 Replace Qwen3.5-35B-A3B
DeepSeek V4 Pro 0423DeepSeek
Coding
38.7
Overall
50.0
Output $/M
$2.976
39
Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
0
vs boards won of 39 shared

DeepSeek V4 Pro 0423 or Qwen3.5-35B-A3B: which to pick

Only DeepSeek V4 Pro 0423 has a coding score, 38.7 on the Vibe Coding Index; Qwen3.5-35B-A3B has none, so the two cannot be ranked on coding.

Pick Qwen3.5-35B-A3B for output tokens 2.3x cheaper ($1.30 vs $2.976 per million).

Model ADeepSeek V4 Pro 0423DeepSeek38.7/1005 independent benchmarks$0.57 per solved taskModel BQwen3.5-35B-A3BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
39
DeepSeek V4 Pro 0423 only
45
Qwen3.5-35B-A3B only
6
Like-for-like categories
7 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 Pro 0423 38.7 from 5 benchmarks, Qwen3.5-35B-A3B not benchmarked.
Widest category
Coding, 21.5 points apart on average over 6 shared benchmarks.
Widest single gap
LMArena WebDev: React: DeepSeek V4 Pro 0423 1441 against Qwen3.5-35B-A3B 1238, 33.8 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Pro 0423 $2.976 against Qwen3.5-35B-A3B $1.30 per million output tokens, 2.3x apart.
Context window
DeepSeek V4 Pro 0423 takes 1.05M tokens, Qwen3.5-35B-A3B 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 V4 Pro 0423BarsQwen3.5-35B-A3BTies
Coding60
Intelligence20
Agentic work10
Reasoning40
Math30
Knowledge40
General190
All shared boards390
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
Coding benchmarks for DeepSeek V4 Pro 0423 and Qwen3.5-35B-A3B
BenchmarkDeepSeek V4 Pro 0423Qwen3.5-35B-A3BLeader
LMArena WebDev14471254DeepSeek V4 Pro 0423
AA Coding Index59.4Not measuredOnly DeepSeek V4 Pro 0423 measured
LiveCodeBench (Vals AI)87.5%Not measuredOnly DeepSeek V4 Pro 0423 measured
SWE-bench Verified (Vals AI)77.4%Not measuredOnly DeepSeek V4 Pro 0423 measured
Terminal-Bench 4 (Vals AI)11.1%Not measuredOnly DeepSeek V4 Pro 0423 measured
Vibe Code Bench (Vals AI)49.9%Not measuredOnly DeepSeek V4 Pro 0423 measured
Code migration (Vals AI)26.2%Not measuredOnly DeepSeek V4 Pro 0423 measured
ProgramBench (Vals AI)0.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
Terminal-Bench 2.1 (Vals AI)50.2%Not measuredOnly DeepSeek V4 Pro 0423 measured
SkillsBench (Vals AI)51.3%Not measuredOnly DeepSeek V4 Pro 0423 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured26.5%Only Qwen3.5-35B-A3B measured
FrontierCode17.6%Not measuredOnly DeepSeek V4 Pro 0423 measured
WeirdML48.9%Not measuredOnly DeepSeek V4 Pro 0423 measured
ALE-Bench1006.1221.8DeepSeek V4 Pro 0423
LMArena Text: coding14701410DeepSeek V4 Pro 0423
LMArena Text: software and IT14691415DeepSeek V4 Pro 0423
LMArena WebDev: React14411238DeepSeek V4 Pro 0423
LMArena WebDev: HTML14351301DeepSeek V4 Pro 0423
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V4 Pro 0423 and Qwen3.5-35B-A3B
BenchmarkDeepSeek V4 Pro 0423Qwen3.5-35B-A3BLeader
AA Intelligence Index30.419.3DeepSeek V4 Pro 0423
Epoch Capabilities Index149.1142.5DeepSeek V4 Pro 0423
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for DeepSeek V4 Pro 0423 and Qwen3.5-35B-A3B
BenchmarkDeepSeek V4 Pro 0423Qwen3.5-35B-A3BLeader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: agents building web apps1000Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: agents building full-stack apps948Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: agents building Godot games1059Not measuredOnly DeepSeek V4 Pro 0423 measured
Finance Agent (Vals AI)44.1%Not measuredOnly DeepSeek V4 Pro 0423 measured
Tax Agent Bench (Vals AI)25.2%Not measuredOnly DeepSeek V4 Pro 0423 measured
Legal Research Bench (Vals AI)23.1%Not measuredOnly DeepSeek V4 Pro 0423 measured
Excel Modeling Benchmark (Vals AI)51.6%Not measuredOnly DeepSeek V4 Pro 0423 measured
τ²-Bench TelecomNot measured89.2%Only Qwen3.5-35B-A3B measured
Vending-Bench 2$3,285$463DeepSeek V4 Pro 0423
Neither model has a result on the other 31 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
Reasoning benchmarks for DeepSeek V4 Pro 0423 and Qwen3.5-35B-A3B
BenchmarkDeepSeek V4 Pro 0423Qwen3.5-35B-A3BLeader
GPQA Diamond89.4%Not measuredOnly DeepSeek V4 Pro 0423 measured
GPQA Diamond (Artificial Analysis run)Not measured84.5%Only Qwen3.5-35B-A3B measured
Humanity's Last Exam (Artificial Analysis run)Not measured21.0%Only Qwen3.5-35B-A3B measured
GPQA Diamond (Epoch AI run)90.9%83.5%DeepSeek V4 Pro 0423
Chess puzzles19.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
Mystery game puzzles17.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text: hard prompts14611400DeepSeek V4 Pro 0423
LMArena Text: expert14631408DeepSeek V4 Pro 0423
LMArena Text: hard prompts in English14661411DeepSeek V4 Pro 0423
Kagi LLM Benchmark53.5%Not measuredOnly DeepSeek V4 Pro 0423 measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for DeepSeek V4 Pro 0423 and Qwen3.5-35B-A3B
BenchmarkDeepSeek V4 Pro 0423Qwen3.5-35B-A3BLeader
OTIS Mock AIME96.7%70.0%DeepSeek V4 Pro 0423
FrontierMath, tiers 1 to 345.3%Not measuredOnly DeepSeek V4 Pro 0423 measured
FrontierMath, tier 42.4%Not measuredOnly DeepSeek V4 Pro 0423 measured
ProofBench16.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text: math14431404DeepSeek V4 Pro 0423
LMArena Text: mathematical work14551410DeepSeek V4 Pro 0423
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for DeepSeek V4 Pro 0423 and Qwen3.5-35B-A3B
BenchmarkDeepSeek V4 Pro 0423Qwen3.5-35B-A3BLeader
MMLU Pro87.3%Not measuredOnly DeepSeek V4 Pro 0423 measured
LegalBench (Vals AI)80.3%Not measuredOnly DeepSeek V4 Pro 0423 measured
CaseLaw (Vals AI)59.4%Not measuredOnly DeepSeek V4 Pro 0423 measured
CorpFin (Vals AI)61.4%Not measuredOnly DeepSeek V4 Pro 0423 measured
TaxEval (Vals AI)72.1%Not measuredOnly DeepSeek V4 Pro 0423 measured
MedCode (Vals AI)40.5%Not measuredOnly DeepSeek V4 Pro 0423 measured
SimpleQA Verified47.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text: science14701413DeepSeek V4 Pro 0423
LMArena Text: medicine and healthcare14661421DeepSeek V4 Pro 0423
LMArena Text: legal and government14641399DeepSeek V4 Pro 0423
LMArena Text: business and finance14431394DeepSeek V4 Pro 0423
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for DeepSeek V4 Pro 0423 and Qwen3.5-35B-A3B
BenchmarkDeepSeek V4 Pro 0423Qwen3.5-35B-A3BLeader
Design Arena: websites1234Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: UI components1219Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: game dev1228Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: data viz1203Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: 3D1253Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: all code categories1240Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: SVG1139Not measuredOnly DeepSeek V4 Pro 0423 measured
Design Arena: ASCII art1149Not measuredOnly DeepSeek V4 Pro 0423 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index190
General benchmarks for DeepSeek V4 Pro 0423 and Qwen3.5-35B-A3B
BenchmarkDeepSeek V4 Pro 0423Qwen3.5-35B-A3BLeader
Public Benefits Bench (Vals AI)62.9%Not measuredOnly DeepSeek V4 Pro 0423 measured
MedScribe (Vals AI)75.1%Not measuredOnly DeepSeek V4 Pro 0423 measured
IFBenchNot measured72.5%Only Qwen3.5-35B-A3B measured
Long context reasoning (AA-LCR)Not measured72.0%Only Qwen3.5-35B-A3B measured
DTBench90.7%80.0%DeepSeek V4 Pro 0423
LMCA41.2%29.5%DeepSeek V4 Pro 0423
Surface Evolver Bench40.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
CL-bench Life13.5%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text14511395DeepSeek V4 Pro 0423
LMArena Text: instruction following14451379DeepSeek V4 Pro 0423
LMArena Text: creative writing14461347DeepSeek V4 Pro 0423
LMArena Text: English14591407DeepSeek V4 Pro 0423
LMArena Text: non-English14391378DeepSeek V4 Pro 0423
LMArena Text: Chinese14811457DeepSeek V4 Pro 0423
LMArena Text: German14581367DeepSeek V4 Pro 0423
LMArena Text: Japanese14461326DeepSeek V4 Pro 0423
LMArena Text: Korean14091355DeepSeek V4 Pro 0423
LMArena Text: French14731412DeepSeek V4 Pro 0423
LMArena Text: Spanish14571390DeepSeek V4 Pro 0423
LMArena Text: Russian14531376DeepSeek V4 Pro 0423
LMArena Text: Polish14611385DeepSeek V4 Pro 0423
LMArena Text: multi-turn14681390DeepSeek V4 Pro 0423
LMArena Text: longer queries14581389DeepSeek V4 Pro 0423
LMArena Text: writing and language14471365DeepSeek V4 Pro 0423
LMArena Text: entertainment and media14311347DeepSeek V4 Pro 0423
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 V4 Pro 0423 and Qwen3.5-35B-A3B
BenchmarkDeepSeek V4 Pro 0423Qwen3.5-35B-A3BLeader
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 Pro 0423$0.0028Fits in one request
Qwen3.5-35B-A3B$0.0008Fits in one request

Qwen3.5-35B-A3B costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Pro 0423$0.077Fits in one request
Qwen3.5-35B-A3B$0.012Fits in one request

Qwen3.5-35B-A3B costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Pro 0423$0.301Fits in one request
Qwen3.5-35B-A3B$0.045Fits in one request

Qwen3.5-35B-A3B 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 Pro 0423 and Qwen3.5-35B-A3B
SpecificationDeepSeek V4 Pro 0423Qwen3.5-35B-A3B
MakerDeepSeekQwen
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026February 25, 2026
Context window1.05M262K
Input $/Mtok$1.358$0.1625
Output $/Mtok$2.976$1.30
Coding index38.7Not benchmarked
Independent measurements behind it51
Cost per solved task$0.57Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Pro 0423 better than Qwen3.5-35B-A3B for coding?

Only DeepSeek V4 Pro 0423 has a coding score, 38.7 on the Vibe Coding Index; Qwen3.5-35B-A3B has none, so the two cannot be ranked on coding. Pick Qwen3.5-35B-A3B for output tokens 2.3x cheaper ($1.30 vs $2.976 per million).

Which is cheaper, DeepSeek V4 Pro 0423 or Qwen3.5-35B-A3B?

DeepSeek V4 Pro 0423 costs $1.358 per million input tokens and $2.976 per million output tokens; Qwen3.5-35B-A3B costs $0.1625 and $1.30. Cost per solved task is known for DeepSeek V4 Pro 0423 only.

Which has the bigger context window, DeepSeek V4 Pro 0423 or Qwen3.5-35B-A3B?

DeepSeek V4 Pro 0423, with 1.05M tokens against 262K.

How many benchmarks is the DeepSeek V4 Pro 0423 vs Qwen3.5-35B-A3B comparison based on?

39 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Pro 0423's coding index rests on 5 independent benchmarks and Qwen3.5-35B-A3B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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