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DeepSeek V3.1 vs DeepSeek V4 Pro 0423

Updated October 21, 2026. 10 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

DeepSeek V3.1DeepSeek
Coding
No data
Overall
13.7
Output $/M
$1.50
0
DeepSeek V4 Pro 0423DeepSeek
Coding
38.7
Overall
30.4
Output $/M
$2.716
10
vs boards won of 10 shared

Decision reading

Only DeepSeek V4 Pro 0423 has a coding score, 38.7 on the Vibe Coding Index; DeepSeek V3.1 has none, so the two cannot be ranked on coding.

DeepSeek V3.1 has the edge where output tokens cost 1.8x less.

Shared results
10
DeepSeek V3.1 only
0
DeepSeek V4 Pro 0423 only
73
Like-for-like categories
3 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 V3.1 not benchmarked, DeepSeek V4 Pro 0423 38.7 from 5 benchmarks.
Widest category
Web design, 17.5 points apart on average over 7 shared benchmarks.
Widest single gap
Design Arena: 3D: DeepSeek V3.1 1077 against DeepSeek V4 Pro 0423 1254, 22.1 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.1 $1.50 against DeepSeek V4 Pro 0423 $2.716 per million output tokens, 1.8x apart.
Context window
DeepSeek V3.1 takes 164K tokens, DeepSeek V4 Pro 0423 1.05M.

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 V3.1BarsDeepSeek V4 Pro 0423Ties
Intelligence01
Web design07
General02
All shared boards010
CodingDirectional onlySix of these boards feed the Vibe Coding Index17 boards, none shared
Coding benchmarks for DeepSeek V3.1 and DeepSeek V4 Pro 0423
BenchmarkDeepSeek V3.1DeepSeek V4 Pro 0423Leader
LMArena WebDevNot measured1447Only DeepSeek V4 Pro 0423 measured
AA Coding IndexNot measured59.4Only DeepSeek V4 Pro 0423 measured
LiveCodeBench (Vals AI)Not measured87.5%Only DeepSeek V4 Pro 0423 measured
SWE-bench Verified (Vals AI)Not measured77.4%Only DeepSeek V4 Pro 0423 measured
Terminal-Bench 4 (Vals AI)Not measured11.1%Only DeepSeek V4 Pro 0423 measured
Vibe Code Bench (Vals AI)Not measured49.9%Only DeepSeek V4 Pro 0423 measured
Code migration (Vals AI)Not measured26.2%Only DeepSeek V4 Pro 0423 measured
ProgramBench (Vals AI)Not measured0.0%Only DeepSeek V4 Pro 0423 measured
Terminal-Bench 2.1 (Vals AI)Not measured50.2%Only DeepSeek V4 Pro 0423 measured
SkillsBench (Vals AI)Not measured51.3%Only DeepSeek V4 Pro 0423 measured
FrontierCodeNot measured17.6%Only DeepSeek V4 Pro 0423 measured
WeirdMLNot measured48.9%Only DeepSeek V4 Pro 0423 measured
ALE-BenchNot measured1006.1Only DeepSeek V4 Pro 0423 measured
LMArena Text: codingNot measured1470Only DeepSeek V4 Pro 0423 measured
LMArena Text: software and ITNot measured1469Only DeepSeek V4 Pro 0423 measured
LMArena WebDev: ReactNot measured1441Only DeepSeek V4 Pro 0423 measured
LMArena WebDev: HTMLNot measured1435Only DeepSeek V4 Pro 0423 measured
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for DeepSeek V3.1 and DeepSeek V4 Pro 0423
BenchmarkDeepSeek V3.1DeepSeek V4 Pro 0423Leader
AA Intelligence Index13.730.4DeepSeek V4 Pro 0423
Epoch Capabilities IndexNot measured149.1Only DeepSeek V4 Pro 0423 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Agentic work benchmarks for DeepSeek V3.1 and DeepSeek V4 Pro 0423
BenchmarkDeepSeek V3.1DeepSeek V4 Pro 0423Leader
AA Agentic IndexNot measured26.3Only DeepSeek V4 Pro 0423 measured
Design Arena: agents building web appsNot measured1000Only DeepSeek V4 Pro 0423 measured
Design Arena: agents building full-stack appsNot measured948Only DeepSeek V4 Pro 0423 measured
Design Arena: agents building Godot gamesNot measured1059Only DeepSeek V4 Pro 0423 measured
Finance Agent (Vals AI)Not measured44.1%Only DeepSeek V4 Pro 0423 measured
Tax Agent Bench (Vals AI)Not measured25.2%Only DeepSeek V4 Pro 0423 measured
Legal Research Bench (Vals AI)Not measured23.1%Only DeepSeek V4 Pro 0423 measured
Excel Modeling Benchmark (Vals AI)Not measured51.6%Only DeepSeek V4 Pro 0423 measured
Vending-Bench 2Not measured$3,285Only DeepSeek V4 Pro 0423 measured
Neither model has a result on the other 30 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Reasoning benchmarks for DeepSeek V3.1 and DeepSeek V4 Pro 0423
BenchmarkDeepSeek V3.1DeepSeek V4 Pro 0423Leader
GPQA DiamondNot measured89.4%Only DeepSeek V4 Pro 0423 measured
GPQA Diamond (Epoch AI run)Not measured90.9%Only DeepSeek V4 Pro 0423 measured
Chess puzzlesNot measured19.0%Only DeepSeek V4 Pro 0423 measured
Mystery game puzzlesNot measured17.0%Only DeepSeek V4 Pro 0423 measured
LMArena Text: hard promptsNot measured1461Only DeepSeek V4 Pro 0423 measured
LMArena Text: expertNot measured1463Only DeepSeek V4 Pro 0423 measured
LMArena Text: hard prompts in EnglishNot measured1466Only DeepSeek V4 Pro 0423 measured
Neither model has a result on the other 14 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Math benchmarks for DeepSeek V3.1 and DeepSeek V4 Pro 0423
BenchmarkDeepSeek V3.1DeepSeek V4 Pro 0423Leader
OTIS Mock AIMENot measured96.7%Only DeepSeek V4 Pro 0423 measured
FrontierMath, tiers 1 to 3Not measured45.3%Only DeepSeek V4 Pro 0423 measured
FrontierMath, tier 4Not measured2.4%Only DeepSeek V4 Pro 0423 measured
ProofBenchNot measured16.0%Only DeepSeek V4 Pro 0423 measured
LMArena Text: mathNot measured1443Only DeepSeek V4 Pro 0423 measured
LMArena Text: mathematical workNot measured1455Only DeepSeek V4 Pro 0423 measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
Knowledge benchmarks for DeepSeek V3.1 and DeepSeek V4 Pro 0423
BenchmarkDeepSeek V3.1DeepSeek V4 Pro 0423Leader
MMLU ProNot measured87.3%Only DeepSeek V4 Pro 0423 measured
LegalBench (Vals AI)Not measured80.3%Only DeepSeek V4 Pro 0423 measured
CaseLaw (Vals AI)Not measured59.4%Only DeepSeek V4 Pro 0423 measured
CorpFin (Vals AI)Not measured61.4%Only DeepSeek V4 Pro 0423 measured
TaxEval (Vals AI)Not measured72.1%Only DeepSeek V4 Pro 0423 measured
MedCode (Vals AI)Not measured40.5%Only DeepSeek V4 Pro 0423 measured
SimpleQA VerifiedNot measured47.0%Only DeepSeek V4 Pro 0423 measured
LMArena Text: scienceNot measured1470Only DeepSeek V4 Pro 0423 measured
LMArena Text: medicine and healthcareNot measured1466Only DeepSeek V4 Pro 0423 measured
LMArena Text: legal and governmentNot measured1464Only DeepSeek V4 Pro 0423 measured
LMArena Text: business and financeNot measured1443Only DeepSeek V4 Pro 0423 measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for DeepSeek V3.1 and DeepSeek V4 Pro 0423
BenchmarkDeepSeek V3.1DeepSeek V4 Pro 0423Leader
Design Arena: websites11231235DeepSeek V4 Pro 0423
Design Arena: UI components10851222DeepSeek V4 Pro 0423
Design Arena: game dev10841229DeepSeek V4 Pro 0423
Design Arena: data viz10951202DeepSeek V4 Pro 0423
Design Arena: 3D10771254DeepSeek V4 Pro 0423
Design Arena: all code categories11121240DeepSeek V4 Pro 0423
Design Arena: SVG9671140DeepSeek V4 Pro 0423
Design Arena: ASCII artNot measured1148Only 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 index02
General benchmarks for DeepSeek V3.1 and DeepSeek V4 Pro 0423
BenchmarkDeepSeek V3.1DeepSeek V4 Pro 0423Leader
Public Benefits Bench (Vals AI)Not measured62.9%Only DeepSeek V4 Pro 0423 measured
MedScribe (Vals AI)Not measured75.1%Only DeepSeek V4 Pro 0423 measured
DTBench82.7%90.7%DeepSeek V4 Pro 0423
LMCA24.3%41.2%DeepSeek V4 Pro 0423
Surface Evolver BenchNot measured40.0%Only DeepSeek V4 Pro 0423 measured
CL-bench LifeNot measured13.5%Only DeepSeek V4 Pro 0423 measured
LMArena TextNot measured1451Only DeepSeek V4 Pro 0423 measured
LMArena Text: instruction followingNot measured1445Only DeepSeek V4 Pro 0423 measured
LMArena Text: creative writingNot measured1446Only DeepSeek V4 Pro 0423 measured
LMArena Text: EnglishNot measured1459Only DeepSeek V4 Pro 0423 measured
LMArena Text: non-EnglishNot measured1439Only DeepSeek V4 Pro 0423 measured
LMArena Text: ChineseNot measured1481Only DeepSeek V4 Pro 0423 measured
LMArena Text: GermanNot measured1458Only DeepSeek V4 Pro 0423 measured
LMArena Text: JapaneseNot measured1446Only DeepSeek V4 Pro 0423 measured
LMArena Text: KoreanNot measured1409Only DeepSeek V4 Pro 0423 measured
LMArena Text: FrenchNot measured1473Only DeepSeek V4 Pro 0423 measured
LMArena Text: SpanishNot measured1457Only DeepSeek V4 Pro 0423 measured
LMArena Text: RussianNot measured1453Only DeepSeek V4 Pro 0423 measured
LMArena Text: PolishNot measured1461Only DeepSeek V4 Pro 0423 measured
LMArena Text: multi-turnNot measured1468Only DeepSeek V4 Pro 0423 measured
LMArena Text: longer queriesNot measured1458Only DeepSeek V4 Pro 0423 measured
LMArena Text: writing and languageNot measured1447Only DeepSeek V4 Pro 0423 measured
LMArena Text: entertainment and mediaNot measured1431Only DeepSeek V4 Pro 0423 measured
Neither model has a result on the other 23 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.1 and DeepSeek V4 Pro 0423
BenchmarkDeepSeek V3.1DeepSeek V4 Pro 0423Leader
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 V3.1$0.0013Fits in one request
DeepSeek V4 Pro 0423$0.0026Fits in one request

DeepSeek V3.1 costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.1$0.032Fits in one request
DeepSeek V4 Pro 0423$0.069Fits in one request

DeepSeek V3.1 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.1$0.125Exceeds the context window
DeepSeek V4 Pro 0423$0.272Fits in one request

DeepSeek V3.1 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 V3.1 and DeepSeek V4 Pro 0423
SpecificationDeepSeek V3.1DeepSeek V4 Pro 0423
MakerDeepSeekDeepSeek
WeightsOpen weightsOpen weights
ReleasedAugust 21, 2025April 24, 2026
Context window164K1.05M
Input $/Mtok$0.55$1.225
Output $/Mtok$1.50$2.716
Coding indexNot benchmarked38.7
Independent measurements behind it05
Cost per solved taskNot computable$0.57
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.1 better than DeepSeek V4 Pro 0423 for coding?

Only DeepSeek V4 Pro 0423 has a coding score, 38.7 on the Vibe Coding Index; DeepSeek V3.1 has none, so the two cannot be ranked on coding. DeepSeek V3.1 has the edge where output tokens cost 1.8x less.

Which is cheaper, DeepSeek V3.1 or DeepSeek V4 Pro 0423?

DeepSeek V3.1 costs $0.55 per million input tokens and $1.50 per million output tokens; DeepSeek V4 Pro 0423 costs $1.225 and $2.716. Cost per solved task is known for DeepSeek V4 Pro 0423 only.

Which has the bigger context window, DeepSeek V3.1 or DeepSeek V4 Pro 0423?

DeepSeek V4 Pro 0423, with 1.05M tokens against 164K.

How many benchmarks is the DeepSeek V3.1 vs DeepSeek V4 Pro 0423 comparison based on?

10 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.1's coding index rests on 0 independent benchmarks and DeepSeek V4 Pro 0423's on 5. Where only one model has a result, the page says so instead of naming a winner.

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