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DeepSeek V4 Pro 0423 vs Qwen3 235B A22B Thinking 2507

DeepSeek V4 Pro 0423 leads Qwen3 235B A22B Thinking 2507 on the Artificial Analysis Intelligence Index, 30.4 to 12.7, at about the same output price ($2.976 vs $3.50 per million). Updated October 22, 2026; 44 benchmarks have a result for both.

Replace DeepSeek V4 Pro 0423 Replace Qwen3 235B A22B Thinking 2507
DeepSeek V4 Pro 0423DeepSeek
Coding
38.7
Overall
50.0
Output $/M
$2.976
43
Qwen3 235B A22B Thinking 2507Qwen
Coding
No data
Overall
52.9
Output $/M
$3.50
1
vs boards won of 44 shared

DeepSeek V4 Pro 0423 or Qwen3 235B A22B Thinking 2507: which to pick

Only DeepSeek V4 Pro 0423 has a coding score, 38.7 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, where it leads.

Model ADeepSeek V4 Pro 0423DeepSeek38.7/1005 independent benchmarks$0.57 per solved taskModel BQwen3 235B A22B Thinking 2507QwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
44
DeepSeek V4 Pro 0423 only
40
Qwen3 235B A22B Thinking 2507 only
2
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 V4 Pro 0423 38.7 from 5 benchmarks, Qwen3 235B A22B Thinking 2507 not benchmarked.
Widest category
Web design, 30.2 points apart on average over 6 shared benchmarks.
Widest single gap
AA Coding Index: DeepSeek V4 Pro 0423 59.4 against Qwen3 235B A22B Thinking 2507 22.1, 37.3 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Pro 0423 $2.976 against Qwen3 235B A22B Thinking 2507 $3.50 per million output tokens, 1.2x apart.
Context window
DeepSeek V4 Pro 0423 takes 1.05M 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 V4 Pro 0423BarsQwen3 235B A22B Thinking 2507Ties
Coding40
Intelligence10
Agentic work20
Reasoning41
Math30
Knowledge50
Web design60
General180
All shared boards431
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for DeepSeek V4 Pro 0423 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V4 Pro 0423Qwen3 235B A22B Thinking 2507Leader
LMArena WebDev1447Not measuredOnly DeepSeek V4 Pro 0423 measured
AA Coding Index59.422.1DeepSeek V4 Pro 0423
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
FrontierCode17.6%Not measuredOnly DeepSeek V4 Pro 0423 measured
WeirdML48.9%41.0%DeepSeek V4 Pro 0423
ALE-Bench1006.1Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text: coding14701424DeepSeek V4 Pro 0423
LMArena Text: software and IT14691431DeepSeek V4 Pro 0423
LMArena WebDev: React1441Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena WebDev: HTML1435Not measuredOnly DeepSeek V4 Pro 0423 measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4 Pro 0423 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V4 Pro 0423Qwen3 235B A22B Thinking 2507Leader
AA Intelligence Index30.412.7DeepSeek V4 Pro 0423
Epoch Capabilities Index149.1Not measuredOnly DeepSeek V4 Pro 0423 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
Agentic work benchmarks for DeepSeek V4 Pro 0423 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V4 Pro 0423Qwen3 235B A22B Thinking 2507Leader
AA Agentic Index26.31.3DeepSeek V4 Pro 0423
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
Vending-Bench 2$3,285-$11DeepSeek V4 Pro 0423
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
Reasoning benchmarks for DeepSeek V4 Pro 0423 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V4 Pro 0423Qwen3 235B A22B Thinking 2507Leader
GPQA Diamond89.4%Not measuredOnly DeepSeek V4 Pro 0423 measured
GPQA Diamond (Epoch AI run)90.9%80.1%DeepSeek V4 Pro 0423
Chess puzzles19.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
Mystery game puzzles17.0%9.0%DeepSeek V4 Pro 0423
LMArena Text: hard prompts14611416DeepSeek V4 Pro 0423
LMArena Text: expert14631463Qwen3 235B A22B Thinking 2507
LMArena Text: hard prompts in English14661432DeepSeek V4 Pro 0423
Kagi LLM Benchmark53.5%Not measuredOnly DeepSeek V4 Pro 0423 measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for DeepSeek V4 Pro 0423 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V4 Pro 0423Qwen3 235B A22B Thinking 2507Leader
OTIS Mock AIME96.7%86.7%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: math14431412DeepSeek V4 Pro 0423
LMArena Text: mathematical work14551435DeepSeek 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 index50
Knowledge benchmarks for DeepSeek V4 Pro 0423 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V4 Pro 0423Qwen3 235B A22B Thinking 2507Leader
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%40.4%DeepSeek V4 Pro 0423
LMArena Text: science14701433DeepSeek V4 Pro 0423
LMArena Text: medicine and healthcare14661456DeepSeek V4 Pro 0423
LMArena Text: legal and government14641415DeepSeek V4 Pro 0423
LMArena Text: business and finance14431413DeepSeek V4 Pro 0423
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for DeepSeek V4 Pro 0423 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V4 Pro 0423Qwen3 235B A22B Thinking 2507Leader
Design Arena: websites12341052DeepSeek V4 Pro 0423
Design Arena: UI components1219942DeepSeek V4 Pro 0423
Design Arena: game dev1228956DeepSeek V4 Pro 0423
Design Arena: data viz1203950DeepSeek V4 Pro 0423
Design Arena: 3D1253997DeepSeek V4 Pro 0423
Design Arena: all code categories12401032DeepSeek V4 Pro 0423
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 index180
General benchmarks for DeepSeek V4 Pro 0423 and Qwen3 235B A22B Thinking 2507
BenchmarkDeepSeek V4 Pro 0423Qwen3 235B A22B Thinking 2507Leader
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
DTBench90.7%80.3%DeepSeek V4 Pro 0423
LMCA41.2%29.3%DeepSeek V4 Pro 0423
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
Surface Evolver Bench40.0%Not measuredOnly DeepSeek V4 Pro 0423 measured
CL-bench Life13.5%Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text14511415DeepSeek V4 Pro 0423
LMArena Text: instruction following14451386DeepSeek V4 Pro 0423
LMArena Text: creative writing14461384DeepSeek V4 Pro 0423
LMArena Text: English14591429DeepSeek V4 Pro 0423
LMArena Text: non-English14391397DeepSeek V4 Pro 0423
LMArena Text: Chinese14811481DeepSeek V4 Pro 0423
LMArena Text: German14581408DeepSeek V4 Pro 0423
LMArena Text: Japanese14461386DeepSeek V4 Pro 0423
LMArena Text: Korean14091375DeepSeek V4 Pro 0423
LMArena Text: French1473Not measuredOnly DeepSeek V4 Pro 0423 measured
LMArena Text: Spanish14571389DeepSeek V4 Pro 0423
LMArena Text: Russian14531401DeepSeek V4 Pro 0423
LMArena Text: Polish14611390DeepSeek V4 Pro 0423
LMArena Text: multi-turn14681406DeepSeek V4 Pro 0423
LMArena Text: longer queries14581400DeepSeek V4 Pro 0423
LMArena Text: writing and language14471388DeepSeek V4 Pro 0423
LMArena Text: entertainment and media14311370DeepSeek 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 235B A22B Thinking 2507
BenchmarkDeepSeek V4 Pro 0423Qwen3 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 V4 Pro 0423$0.0028Fits in one request
Qwen3 235B A22B Thinking 2507$0.0022Fits in one request

Qwen3 235B A22B Thinking 2507 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Pro 0423$0.077Fits in one request
Qwen3 235B A22B Thinking 2507$0.033Fits in one request

Qwen3 235B A22B Thinking 2507 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Pro 0423$0.301Fits in one request
Qwen3 235B A22B Thinking 2507$0.125Exceeds the context window

Qwen3 235B A22B Thinking 2507 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 235B A22B Thinking 2507
SpecificationDeepSeek V4 Pro 0423Qwen3 235B A22B Thinking 2507
MakerDeepSeekQwen
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026July 25, 2025
Context window1.05M128K
Input $/Mtok$1.358$0.45
Output $/Mtok$2.976$3.50
Coding index38.7Not benchmarked
Independent measurements behind it50
Cost per solved task$0.57Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Pro 0423 better than Qwen3 235B A22B Thinking 2507 for coding?

Only DeepSeek V4 Pro 0423 has a coding score, 38.7 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, where it leads.

Which is cheaper, DeepSeek V4 Pro 0423 or Qwen3 235B A22B Thinking 2507?

DeepSeek V4 Pro 0423 costs $1.358 per million input tokens and $2.976 per million output tokens; Qwen3 235B A22B Thinking 2507 costs $0.45 and $3.50. Cost per solved task is known for DeepSeek V4 Pro 0423 only.

Which has the bigger context window, DeepSeek V4 Pro 0423 or Qwen3 235B A22B Thinking 2507?

DeepSeek V4 Pro 0423, with 1.05M tokens against 128K.

How many benchmarks is the DeepSeek V4 Pro 0423 vs Qwen3 235B A22B Thinking 2507 comparison based on?

44 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 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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