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R1 0528 vs Grok 4.3

Grok 4.3 leads R1 0528 on the Artificial Analysis Intelligence Index, 24.9 to 13.1, at about the same output price ($2.50 vs $2.18 per million). Updated October 22, 2026; 46 benchmarks have a result for both.

R1 0528DeepSeek
Coding
No data
Overall
46.8
Output $/M
$2.18
27
Grok 4.3xAI
Coding
37.4
Overall
53.1
Output $/M
$2.50
19
vs boards won of 46 shared

R1 0528 or Grok 4.3: which to pick

Only Grok 4.3 has a coding score, 37.4 on the Vibe Coding Index; R1 0528 has none, so the two cannot be ranked on coding.

Pick R1 0528 for output tokens 1.1x cheaper ($2.18 vs $2.50 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Shared results
46
R1 0528 only
14
Grok 4.3 only
59
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
R1 0528 not benchmarked, Grok 4.3 37.4 from 3 benchmarks.
Widest category
Agentic work, 61.1 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: R1 0528 36.5% against Grok 4.3 97.7%, 61.1 points apart on a 0 to 100 scale.
Output price
R1 0528 $2.18 against Grok 4.3 $2.50 per million output tokens, 1.1x apart.
Context window
R1 0528 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
CategoryR1 0528BarsGrok 4.3Ties
Coding23
Intelligence01
Agentic work01
Reasoning33
Math21
Knowledge40
Web design16
General154
All shared boards2719
CodingLike-for-likeSix of these boards feed the Vibe Coding Index23
Coding benchmarks for R1 0528 and Grok 4.3
BenchmarkR1 0528Grok 4.3Leader
Aider polyglot71.4%Not measuredOnly R1 0528 measured
LMArena WebDevNot measured1358Only Grok 4.3 measured
AA Coding IndexNot measured42.2Only Grok 4.3 measured
LiveCodeBench (Vals AI)Not measured84.5%Only Grok 4.3 measured
SWE-bench Verified (Vals AI)Not measured71.4%Only Grok 4.3 measured
Vibe Code Bench (Vals AI)Not measured19.4%Only Grok 4.3 measured
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)77.0%Not measuredOnly R1 0528 measured
SciCodeNot measured48.3%Only Grok 4.3 measured
Terminal-Bench Hard (Artificial Analysis run)15.9%37.9%Grok 4.3
WeirdML41.6%49.9%Grok 4.3
ALE-Bench804.1944.2Grok 4.3
LMArena Text: coding14271415R1 0528
LMArena Text: software and IT14351416R1 0528
LMArena WebDev: ReactNot measured1353Only Grok 4.3 measured
LMArena WebDev: HTMLNot measured1367Only Grok 4.3 measured
LMArena WebDev: from an imageNot measured1375Only Grok 4.3 measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for R1 0528 and Grok 4.3
BenchmarkR1 0528Grok 4.3Leader
AA Intelligence Index13.124.9Grok 4.3
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for R1 0528 and Grok 4.3
BenchmarkR1 0528Grok 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 measured1058Only Grok 4.3 measured
Design Arena: agents building Android appsNot measured962Only 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 measured959Only Grok 4.3 measured
Design Arena: PowerPoint slidesNot measured988Only Grok 4.3 measured
Design Arena: spreadsheetsNot measured879Only 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 Telecom36.5%97.7%Grok 4.3
METR time horizons53.8%Not measuredOnly R1 0528 measured
DeepResearch Bench35.1%Not measuredOnly R1 0528 measured
Vending-Bench 2Not measured$35Only Grok 4.3 measured
LMArena SearchNot measured1166Only Grok 4.3 measured
BrowseComp-Plus16.4%Not measuredOnly R1 0528 measured
Neither model has a result on the other 21 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index33
Reasoning benchmarks for R1 0528 and Grok 4.3
BenchmarkR1 0528Grok 4.3Leader
GPQA DiamondNot measured91.4%Only Grok 4.3 measured
MMMU Pro (Vals AI)Not measured83.1%Only Grok 4.3 measured
GPQA Diamond (Artificial Analysis run)81.3%90.1%Grok 4.3
Humanity's Last Exam (Artificial Analysis run)15.8%37.2%Grok 4.3
GPQA Diamond (Epoch AI run)76.3%88.8%Grok 4.3
ARC-AGI21.2%Not measuredOnly R1 0528 measured
ARC-AGI-21.1%Not measuredOnly R1 0528 measured
SimpleBench40.8%Not measuredOnly R1 0528 measured
Chess puzzlesNot measured18.0%Only Grok 4.3 measured
LMArena Text: hard prompts14151396R1 0528
LMArena Text: expert13941384R1 0528
LMArena Text: hard prompts in English14221402R1 0528
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 index21
Math benchmarks for R1 0528 and Grok 4.3
BenchmarkR1 0528Grok 4.3Leader
AA Math Index76.0Not measuredOnly R1 0528 measured
AIME 2025 (Artificial Analysis run)76.0%Not measuredOnly R1 0528 measured
OTIS Mock AIME66.4%93.3%Grok 4.3
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
MATH level 596.6%Not measuredOnly R1 0528 measured
LMArena Text: math14001387R1 0528
LMArena Text: mathematical work14151396R1 0528
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for R1 0528 and Grok 4.3
BenchmarkR1 0528Grok 4.3Leader
MMLU ProNot measured85.8%Only Grok 4.3 measured
LegalBench (Vals AI)Not measured84.5%Only Grok 4.3 measured
CaseLaw (Vals AI)Not measured79.3%Only Grok 4.3 measured
CorpFin (Vals AI)Not measured68.5%Only Grok 4.3 measured
TaxEval (Vals AI)Not measured70.8%Only Grok 4.3 measured
MortgageTax (Vals AI)Not measured48.3%Only Grok 4.3 measured
MedCode (Vals AI)Not measured38.1%Only Grok 4.3 measured
MMLU Pro (Artificial Analysis run)84.9%Not measuredOnly R1 0528 measured
SimpleQA VerifiedNot measured33.2%Only Grok 4.3 measured
LMArena Text: science14301399R1 0528
LMArena Text: medicine and healthcare14451384R1 0528
LMArena Text: legal and government14191386R1 0528
LMArena Text: business and finance14021381R1 0528
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index16
Web design benchmarks for R1 0528 and Grok 4.3
BenchmarkR1 0528Grok 4.3Leader
Design Arena: websites11491196Grok 4.3
Design Arena: UI components11001190Grok 4.3
Design Arena: game dev10971173Grok 4.3
Design Arena: data viz11821179R1 0528
Design Arena: 3D11101124Grok 4.3
Design Arena: all code categories11381186Grok 4.3
Design Arena: SVG10381080Grok 4.3
Design Arena: ASCII artNot measured1125Only Grok 4.3 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index154
General benchmarks for R1 0528 and Grok 4.3
BenchmarkR1 0528Grok 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
IFBench39.6%83.3%Grok 4.3
Long context reasoning (AA-LCR)55.7%75.0%Grok 4.3
DTBenchNot measured90.7%Only Grok 4.3 measured
LMCANot measured38.3%Only Grok 4.3 measured
Fiction.LiveBench75.0%Not measuredOnly R1 0528 measured
Creative writing (Lech Mazur)81.9%Not measuredOnly R1 0528 measured
LMArena Text14281397R1 0528
LMArena Text: instruction following13821366R1 0528
LMArena Text: creative writing14051380R1 0528
LMArena VisionNot measured1229Only Grok 4.3 measured
LMArena Text: English14371404R1 0528
LMArena Text: non-English14121385R1 0528
LMArena Text: Chinese14421422R1 0528
LMArena Text: German14041395R1 0528
LMArena Text: Japanese13911379R1 0528
LMArena Text: Korean13601354R1 0528
LMArena Text: French14171411R1 0528
LMArena Text: Spanish14111399R1 0528
LMArena Text: Russian14231399R1 0528
LMArena Text: Polish14281398R1 0528
LMArena Text: multi-turn14051406Grok 4.3
LMArena Text: longer queries13911393Grok 4.3
LMArena Text: writing and language14021385R1 0528
LMArena Text: entertainment and media14001370R1 0528
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 R1 0528 and Grok 4.3
BenchmarkR1 0528Grok 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

R1 0528$0.0016Fits in one request
Grok 4.3$0.0025Fits in one request

R1 0528 costs less

Repository review

50K input + 3K output tokens

R1 0528$0.032Fits in one request
Grok 4.3$0.070Fits in one request

R1 0528 costs less

Agent loop

200K input + 10K output tokens

R1 0528$0.122Exceeds the context window
Grok 4.3$0.275Fits in one request

R1 0528 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 R1 0528 and Grok 4.3
SpecificationDeepSeek R1 0528SpaceXAI Grok 4.3
MakerDeepSeekxAI
WeightsOpen weightsNo public weights listed
ReleasedMay 28, 2025April 30, 2026
Context window164K1M
Input $/Mtok$0.50$1.25
Output $/Mtok$2.18$2.50
Coding indexNot benchmarked37.4
Independent measurements behind it03
Cost per solved taskNot computable$0.31
SourceOpenRouter listingOpenRouter listing

Questions

Is R1 0528 better than Grok 4.3 for coding?

Only Grok 4.3 has a coding score, 37.4 on the Vibe Coding Index; R1 0528 has none, so the two cannot be ranked on coding. Pick R1 0528 for output tokens 1.1x cheaper ($2.18 vs $2.50 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, R1 0528 or Grok 4.3?

R1 0528 costs $0.50 per million input tokens and $2.18 per million output tokens; Grok 4.3 costs $1.25 and $2.50. Cost per solved task is known for Grok 4.3 only.

Which has the bigger context window, R1 0528 or Grok 4.3?

Grok 4.3, with 1M tokens against 164K.

How many benchmarks is the R1 0528 vs Grok 4.3 comparison based on?

46 benchmarks have a result for both models as of October 22, 2026. R1 0528's coding index rests on 0 independent benchmarks and Grok 4.3's on 3. Where only one model has a result, the page says so instead of naming a winner.

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