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DeepSeek V3.2 vs Grok 4.3

Updated October 21, 2026. 59 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

DeepSeek V3.2DeepSeek
Coding
54.4
Overall
21.5
Output $/M
$0.42
32
Grok 4.3xAI
Coding
22.5
Overall
24.9
Output $/M
$2.50
27
vs boards won of 59 shared

Decision reading

Pick DeepSeek V3.2 for coding: it scores 54.4 on the Vibe Coding Index against 22.5 for Grok 4.3.

Pick Grok 4.3 when a solved task costs $0.31 against $0.99, or when the context window is larger, 1M against 164K tokens.

Shared results
59
DeepSeek V3.2 only
16
Grok 4.3 only
45
Like-for-like categories
8 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 V3.2 54.4 from 2 benchmarks, Grok 4.3 22.5 from 1 benchmark.
Widest category
Knowledge, 9.1 points apart on average over 9 shared benchmarks.
Widest single gap
CaseLaw (Vals AI): DeepSeek V3.2 55.4% against Grok 4.3 79.3%, 23.9 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 $0.42 against Grok 4.3 $2.50 per million output tokens, 6.0x apart.
Context window
DeepSeek V3.2 takes 164K tokens, Grok 4.3 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 V3.2BarsGrok 4.3Ties
Coding55
Intelligence01
Agentic work11
Reasoning33
Math20
Knowledge45
Web design17
General165
All shared boards3227
CodingLike-for-likeFour of these boards feed the Vibe Coding Index55
Coding benchmarks for DeepSeek V3.2 and Grok 4.3
BenchmarkDeepSeek V3.2Grok 4.3Leader
SWE-bench Verified70.0%Not measuredOnly DeepSeek V3.2 measured
SWE-bench Multilingual59.0%Not measuredOnly DeepSeek V3.2 measured
LMArena WebDev13621358DeepSeek V3.2
AA Coding Index44.242.2DeepSeek V3.2
LiveCodeBench (Vals AI)80.7%84.5%Grok 4.3
SWE-bench Verified (Vals AI)67.6%71.4%Grok 4.3
Vibe Code Bench (Vals AI)5.1%19.4%Grok 4.3
Code migration (Vals AI)Not measured6.8%Only Grok 4.3 measured
ProgramBench (Vals AI)Not measured0.0%Only Grok 4.3 measured
Terminal-Bench 2.1 (Vals AI)Not measured42.0%Only Grok 4.3 measured
SkillsBench (Vals AI)Not measured40.6%Only Grok 4.3 measured
LiveCodeBench (Artificial Analysis run)86.2%Not measuredOnly DeepSeek V3.2 measured
SciCodeNot measured48.3%Only Grok 4.3 measured
Terminal-Bench Hard (Artificial Analysis run)35.6%37.9%Grok 4.3
Terminal-Bench39.6%Not measuredOnly DeepSeek V3.2 measured
WeirdMLNot measured49.9%Only Grok 4.3 measured
ALE-BenchNot measured944.2Only Grok 4.3 measured
LMArena Text: coding14531415DeepSeek V3.2
LMArena Text: software and IT14491416DeepSeek V3.2
LMArena WebDev: React13501353Grok 4.3
LMArena WebDev: HTML13711367DeepSeek V3.2
LMArena WebDev: from an imageNot measured1375Only Grok 4.3 measured
Neither model has a result on the other 16 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for DeepSeek V3.2 and Grok 4.3
BenchmarkDeepSeek V3.2Grok 4.3Leader
AA Intelligence Index21.524.9Grok 4.3
Epoch Capabilities Index146.1Not measuredOnly DeepSeek V3.2 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index11
Agentic work benchmarks for DeepSeek V3.2 and Grok 4.3
BenchmarkDeepSeek V3.2Grok 4.3Leader
AA Agentic IndexNot measured15.5Only Grok 4.3 measured
Design Arena: agents building web appsNot measured1126Only Grok 4.3 measured
Design Arena: agents building full-stack appsNot measured1006Only Grok 4.3 measured
Design Arena: agents building mobile appsNot measured1059Only Grok 4.3 measured
Design Arena: agents building Android appsNot measured967Only Grok 4.3 measured
Design Arena: agents building Godot gamesNot measured914Only Grok 4.3 measured
Design Arena: agents building gamesNot measured1007Only Grok 4.3 measured
Design Arena: HTML slidesNot measured1008Only Grok 4.3 measured
Design Arena: PowerPoint slidesNot measured1012Only Grok 4.3 measured
Finance Agent (Vals AI)Not measured37.7%Only Grok 4.3 measured
Tax Agent Bench (Vals AI)Not measured6.2%Only Grok 4.3 measured
Legal Research Bench (Vals AI)Not measured15.4%Only Grok 4.3 measured
Excel Modeling Benchmark (Vals AI)Not measured18.4%Only Grok 4.3 measured
τ²-Bench Telecom90.6%97.7%Grok 4.3
APEX-Agents21.3%Not measuredOnly DeepSeek V3.2 measured
Vending-Bench 2$1,034$35DeepSeek V3.2
LMArena SearchNot measured1166Only Grok 4.3 measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index33
Reasoning benchmarks for DeepSeek V3.2 and Grok 4.3
BenchmarkDeepSeek V3.2Grok 4.3Leader
GPQA Diamond80.3%91.4%Grok 4.3
MMMU Pro (Vals AI)Not measured83.1%Only Grok 4.3 measured
GPQA Diamond (Artificial Analysis run)84.0%90.1%Grok 4.3
Humanity's Last Exam (Artificial Analysis run)24.6%37.2%Grok 4.3
GPQA Diamond (Epoch AI run)Not measured88.8%Only Grok 4.3 measured
ARC-AGI57.0%Not measuredOnly DeepSeek V3.2 measured
ARC-AGI-24.0%Not measuredOnly DeepSeek V3.2 measured
Chess puzzlesNot measured18.0%Only Grok 4.3 measured
LMArena Text: hard prompts14341396DeepSeek V3.2
LMArena Text: expert14361384DeepSeek V3.2
LMArena Text: hard prompts in English14461402DeepSeek V3.2
LMArena Vision: diagramsNot measured1241Only Grok 4.3 measured
LMArena Vision: homeworkNot measured1241Only Grok 4.3 measured
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V3.2 and Grok 4.3
BenchmarkDeepSeek V3.2Grok 4.3Leader
AIME84.6%Not measuredOnly DeepSeek V3.2 measured
MGSM (Vals AI)86.0%Not measuredOnly DeepSeek V3.2 measured
AA Math Index92.0Not measuredOnly DeepSeek V3.2 measured
AIME 2025 (Artificial Analysis run)92.0%Not measuredOnly DeepSeek V3.2 measured
OTIS Mock AIMENot measured93.3%Only Grok 4.3 measured
FrontierMath, tiers 1 to 3Not measured42.8%Only Grok 4.3 measured
FrontierMath, tier 4Not measured14.6%Only Grok 4.3 measured
ProofBenchNot measured11.0%Only Grok 4.3 measured
LMArena Text: math14351387DeepSeek V3.2
LMArena Text: mathematical work14401396DeepSeek V3.2
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index45
Knowledge benchmarks for DeepSeek V3.2 and Grok 4.3
BenchmarkDeepSeek V3.2Grok 4.3Leader
MMLU Pro84.9%85.8%Grok 4.3
LegalBench (Vals AI)76.1%84.5%Grok 4.3
CaseLaw (Vals AI)55.4%79.3%Grok 4.3
CorpFin (Vals AI)51.0%68.5%Grok 4.3
TaxEval (Vals AI)68.2%70.8%Grok 4.3
MortgageTax (Vals AI)Not measured48.3%Only Grok 4.3 measured
MedQA (Vals AI)93.9%Not measuredOnly DeepSeek V3.2 measured
MedCode (Vals AI)Not measured38.1%Only Grok 4.3 measured
MMLU Pro (Artificial Analysis run)86.2%Not measuredOnly DeepSeek V3.2 measured
SimpleQA VerifiedNot measured33.2%Only Grok 4.3 measured
LMArena Text: science14461399DeepSeek V3.2
LMArena Text: medicine and healthcare14401384DeepSeek V3.2
LMArena Text: legal and government14251386DeepSeek V3.2
LMArena Text: business and finance14101381DeepSeek V3.2
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index17
Web design benchmarks for DeepSeek V3.2 and Grok 4.3
BenchmarkDeepSeek V3.2Grok 4.3Leader
Design Arena: websites11751196Grok 4.3
Design Arena: UI components11491192Grok 4.3
Design Arena: game dev11321174Grok 4.3
Design Arena: data viz11581180Grok 4.3
Design Arena: 3D11331125DeepSeek V3.2
Design Arena: all code categories11641187Grok 4.3
Design Arena: SVG10321081Grok 4.3
Design Arena: ASCII art10821125Grok 4.3
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index165
General benchmarks for DeepSeek V3.2 and Grok 4.3
BenchmarkDeepSeek V3.2Grok 4.3Leader
Public Benefits Bench (Vals AI)Not measured51.7%Only Grok 4.3 measured
SAGE (Vals AI)Not measured19.7%Only Grok 4.3 measured
MedScribe (Vals AI)Not measured74.4%Only Grok 4.3 measured
Vals Multimodal IndexNot measured43.3%Only Grok 4.3 measured
IFBench60.7%83.3%Grok 4.3
Long context reasoning (AA-LCR)73.3%75.0%Grok 4.3
DTBench85.6%90.7%Grok 4.3
LMCA28.8%38.3%Grok 4.3
CL-bench12.4%Not measuredOnly DeepSeek V3.2 measured
CL-bench Life7.4%Not measuredOnly DeepSeek V3.2 measured
LMArena Text14251397DeepSeek V3.2
LMArena Text: instruction following14131366DeepSeek V3.2
LMArena Text: creative writing14001380DeepSeek V3.2
LMArena VisionNot measured1229Only Grok 4.3 measured
LMArena Text: English14391404DeepSeek V3.2
LMArena Text: non-English14091385DeepSeek V3.2
LMArena Text: Chinese14551422DeepSeek V3.2
LMArena Text: German14131395DeepSeek V3.2
LMArena Text: Japanese13741379Grok 4.3
LMArena Text: Korean13701354DeepSeek V3.2
LMArena Text: French14291411DeepSeek V3.2
LMArena Text: Spanish14241399DeepSeek V3.2
LMArena Text: Russian14241399DeepSeek V3.2
LMArena Text: Polish14191398DeepSeek V3.2
LMArena Text: multi-turn14271406DeepSeek V3.2
LMArena Text: longer queries14281393DeepSeek V3.2
LMArena Text: writing and language14071385DeepSeek V3.2
LMArena Text: entertainment and media13951370DeepSeek V3.2
LMArena Vision: EnglishNot measured1235Only Grok 4.3 measured
LMArena Vision: ChineseNot measured1257Only Grok 4.3 measured
LMArena Vision: reading textNot measured1235Only Grok 4.3 measured
LMArena Vision: humorNot measured1222Only Grok 4.3 measured
LMArena Vision: recognizing thingsNot measured1217Only Grok 4.3 measured
LMArena Vision: creative writingNot measured1237Only Grok 4.3 measured
Neither model has a result on the other 12 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.2 and Grok 4.3
BenchmarkDeepSeek V3.2Grok 4.3Leader
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$0.0005Fits in one request
Grok 4.3$0.0025Fits in one request

DeepSeek V3.2 costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2$0.015Fits in one request
Grok 4.3$0.070Fits in one request

DeepSeek V3.2 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2$0.060Exceeds the context window
Grok 4.3$0.275Fits in one request

DeepSeek V3.2 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 and Grok 4.3
SpecificationDeepSeek V3.2SpaceXAI Grok 4.3
MakerDeepSeekxAI
WeightsOpen weightsNo public weights listed
ReleasedDecember 1, 2025April 30, 2026
Context window164K1M
Input $/Mtok$0.28$1.25
Output $/Mtok$0.42$2.50
Coding index54.422.5
Independent measurements behind it21
Cost per solved task$0.99$0.31
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 better than Grok 4.3 for coding?

Pick DeepSeek V3.2 for coding: it scores 54.4 on the Vibe Coding Index against 22.5 for Grok 4.3. Pick Grok 4.3 when a solved task costs $0.31 against $0.99, or when the context window is larger, 1M against 164K tokens.

Which is cheaper, DeepSeek V3.2 or Grok 4.3?

DeepSeek V3.2 costs $0.28 per million input tokens and $0.42 per million output tokens; Grok 4.3 costs $1.25 and $2.50. Per solved SWE-bench Verified task, DeepSeek V3.2 costs $0.99 and Grok 4.3 $0.31.

Which has the bigger context window, DeepSeek V3.2 or Grok 4.3?

Grok 4.3, with 1M tokens against 164K.

How many benchmarks is the DeepSeek V3.2 vs Grok 4.3 comparison based on?

59 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.2's coding index rests on 2 independent benchmarks and Grok 4.3's on 1. Where only one model has a result, the page says so instead of naming a winner.

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