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R1 0528 vs Kimi K2.7 Code

Kimi K2.7 Code leads R1 0528 on the Artificial Analysis Intelligence Index, 25.8 to 13.1, and R1 0528 costs 1.8x less per output token ($2.18 vs $4.00 per million). Updated October 22, 2026; 19 benchmarks have a result for both.

Replace R1 0528 Replace Kimi K2.7 Code
R1 0528DeepSeek
Coding
No data
Overall
46.8
Output $/M
$2.18
0
Kimi K2.7 CodeMoonshot AI
Coding
53.4
Overall
56.7
Output $/M
$4.00
19
vs boards won of 19 shared

R1 0528 or Kimi K2.7 Code: which to pick

Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; R1 0528 has none, so the two cannot be ranked on coding.

Pick R1 0528 for output tokens 1.8x cheaper ($2.18 vs $4.00 per million).

Model AR1 0528DeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BKimi K2.7 CodeMoonshot AI53.4/1004 independent benchmarks$0.35 per solved task
Shared results
19
R1 0528 only
41
Kimi K2.7 Code only
32
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
R1 0528 not benchmarked, Kimi K2.7 Code 53.4 from 4 benchmarks.
Widest category
Agentic work, 53.5 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: R1 0528 36.5% against Kimi K2.7 Code 90.1%, 53.5 points apart on a 0 to 100 scale.
Output price
R1 0528 $2.18 against Kimi K2.7 Code $4.00 per million output tokens, 1.8x apart.
Context window
R1 0528 takes 164K tokens, Kimi K2.7 Code 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
CategoryR1 0528BarsKimi K2.7 CodeTies
Coding03
Intelligence01
Agentic work01
Reasoning04
Math01
Web design07
General02
All shared boards019
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for R1 0528 and Kimi K2.7 Code
BenchmarkR1 0528Kimi K2.7 CodeLeader
Aider polyglot71.4%Not measuredOnly R1 0528 measured
LMArena WebDevNot measured1474Only Kimi K2.7 Code measured
AA Coding IndexNot measured60.8Only Kimi K2.7 Code measured
LiveCodeBench (Vals AI)Not measured82.0%Only Kimi K2.7 Code measured
SWE-bench Verified (Vals AI)Not measured78.2%Only Kimi K2.7 Code measured
Vibe Code Bench (Vals AI)Not measured47.2%Only Kimi K2.7 Code measured
Code migration (Vals AI)Not measured25.4%Only Kimi K2.7 Code measured
ProgramBench (Vals AI)Not measured0.0%Only Kimi K2.7 Code measured
Terminal-Bench 2.1 (Vals AI)Not measured67.0%Only Kimi K2.7 Code measured
SkillsBench (Vals AI)Not measured50.0%Only Kimi K2.7 Code measured
LiveCodeBench (Artificial Analysis run)77.0%Not measuredOnly R1 0528 measured
SciCodeNot measured47.8%Only Kimi K2.7 Code measured
Terminal-Bench Hard (Artificial Analysis run)15.9%44.7%Kimi K2.7 Code
FrontierCodeNot measured30.1%Only Kimi K2.7 Code measured
WeirdML41.6%54.1%Kimi K2.7 Code
ALE-Bench804.1886.2Kimi K2.7 Code
LMArena Text: coding1427Not measuredOnly R1 0528 measured
LMArena Text: software and IT1435Not measuredOnly R1 0528 measured
LMArena WebDev: ReactNot measured1475Only Kimi K2.7 Code measured
LMArena WebDev: HTMLNot measured1451Only Kimi K2.7 Code measured
LMArena WebDev: from an imageNot measured1513Only Kimi K2.7 Code measured
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for R1 0528 and Kimi K2.7 Code
BenchmarkR1 0528Kimi K2.7 CodeLeader
AA Intelligence Index13.125.8Kimi K2.7 Code
Epoch Capabilities IndexNot measured150.1Only Kimi K2.7 Code measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for R1 0528 and Kimi K2.7 Code
BenchmarkR1 0528Kimi K2.7 CodeLeader
AA Agentic IndexNot measured21.0Only Kimi K2.7 Code measured
Design Arena: agents building web appsNot measured1176Only Kimi K2.7 Code measured
Design Arena: agents building full-stack appsNot measured1175Only Kimi K2.7 Code measured
Design Arena: agents building mobile appsNot measured1143Only Kimi K2.7 Code measured
Design Arena: agents building Android appsNot measured1138Only Kimi K2.7 Code measured
Design Arena: agents building Godot gamesNot measured1147Only Kimi K2.7 Code measured
Design Arena: agents building gamesNot measured1130Only Kimi K2.7 Code measured
Design Arena: HTML slidesNot measured1151Only Kimi K2.7 Code measured
Design Arena: PowerPoint slidesNot measured1129Only Kimi K2.7 Code measured
τ²-Bench Telecom36.5%90.1%Kimi K2.7 Code
APEX-AgentsNot measured37.6%Only Kimi K2.7 Code measured
METR time horizons53.8%Not measuredOnly R1 0528 measured
DeepResearch Bench35.1%Not measuredOnly R1 0528 measured
Vending-Bench 2Not measured$5,083Only Kimi K2.7 Code measured
BrowseComp-Plus16.4%Not measuredOnly R1 0528 measured
Neither model has a result on the other 26 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for R1 0528 and Kimi K2.7 Code
BenchmarkR1 0528Kimi K2.7 CodeLeader
GPQA Diamond (Artificial Analysis run)81.3%89.6%Kimi K2.7 Code
Humanity's Last Exam (Artificial Analysis run)15.8%35.0%Kimi K2.7 Code
GPQA Diamond (Epoch AI run)76.3%87.9%Kimi K2.7 Code
ARC-AGI21.2%Not measuredOnly R1 0528 measured
ARC-AGI-21.1%Not measuredOnly R1 0528 measured
SimpleBench40.8%57.9%Kimi K2.7 Code
Chess puzzlesNot measured14.0%Only Kimi K2.7 Code measured
LMArena Text: hard prompts1415Not measuredOnly R1 0528 measured
LMArena Text: expert1394Not measuredOnly R1 0528 measured
LMArena Text: hard prompts in English1422Not measuredOnly R1 0528 measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index01
Math benchmarks for R1 0528 and Kimi K2.7 Code
BenchmarkR1 0528Kimi K2.7 CodeLeader
AA Math Index76.0Not measuredOnly R1 0528 measured
AIME 2025 (Artificial Analysis run)76.0%Not measuredOnly R1 0528 measured
OTIS Mock AIME66.4%95.6%Kimi K2.7 Code
FrontierMath, tiers 1 to 3Not measured54.0%Only Kimi K2.7 Code measured
FrontierMath, tier 4Not measured12.2%Only Kimi K2.7 Code measured
MATH level 596.6%Not measuredOnly R1 0528 measured
LMArena Text: math1400Not measuredOnly R1 0528 measured
LMArena Text: mathematical work1415Not measuredOnly R1 0528 measured
Neither model has a result on the other 5 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Knowledge benchmarks for R1 0528 and Kimi K2.7 Code
BenchmarkR1 0528Kimi K2.7 CodeLeader
MMLU Pro (Artificial Analysis run)84.9%Not measuredOnly R1 0528 measured
SimpleQA VerifiedNot measured36.5%Only Kimi K2.7 Code measured
LMArena Text: science1430Not measuredOnly R1 0528 measured
LMArena Text: medicine and healthcare1445Not measuredOnly R1 0528 measured
LMArena Text: legal and government1419Not measuredOnly R1 0528 measured
LMArena Text: business and finance1402Not measuredOnly R1 0528 measured
Neither model has a result on the other 12 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for R1 0528 and Kimi K2.7 Code
BenchmarkR1 0528Kimi K2.7 CodeLeader
Design Arena: websites11491263Kimi K2.7 Code
Design Arena: UI components11001255Kimi K2.7 Code
Design Arena: game dev10971220Kimi K2.7 Code
Design Arena: data viz11821227Kimi K2.7 Code
Design Arena: 3D11101240Kimi K2.7 Code
Design Arena: all code categories11381252Kimi K2.7 Code
Design Arena: SVG10381176Kimi K2.7 Code
Design Arena: ASCII artNot measured1196Only Kimi K2.7 Code 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 R1 0528 and Kimi K2.7 Code
BenchmarkR1 0528Kimi K2.7 CodeLeader
IFBench39.6%63.1%Kimi K2.7 Code
Long context reasoning (AA-LCR)55.7%79.3%Kimi K2.7 Code
Fiction.LiveBench75.0%Not measuredOnly R1 0528 measured
Creative writing (Lech Mazur)81.9%Not measuredOnly R1 0528 measured
Surface Evolver BenchNot measured48.8%Only Kimi K2.7 Code measured
LMArena Text1428Not measuredOnly R1 0528 measured
LMArena Text: instruction following1382Not measuredOnly R1 0528 measured
LMArena Text: creative writing1405Not measuredOnly R1 0528 measured
LMArena Text: English1437Not measuredOnly R1 0528 measured
LMArena Text: non-English1412Not measuredOnly R1 0528 measured
LMArena Text: Chinese1442Not measuredOnly R1 0528 measured
LMArena Text: German1404Not measuredOnly R1 0528 measured
LMArena Text: Japanese1391Not measuredOnly R1 0528 measured
LMArena Text: Korean1360Not measuredOnly R1 0528 measured
LMArena Text: French1417Not measuredOnly R1 0528 measured
LMArena Text: Spanish1411Not measuredOnly R1 0528 measured
LMArena Text: Russian1423Not measuredOnly R1 0528 measured
LMArena Text: Polish1428Not measuredOnly R1 0528 measured
LMArena Text: multi-turn1405Not measuredOnly R1 0528 measured
LMArena Text: longer queries1391Not measuredOnly R1 0528 measured
LMArena Text: writing and language1402Not measuredOnly R1 0528 measured
LMArena Text: entertainment and media1400Not measuredOnly R1 0528 measured
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for R1 0528 and Kimi K2.7 Code
BenchmarkR1 0528Kimi K2.7 CodeLeader
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
Kimi K2.7 Code$0.0029Fits in one request

R1 0528 costs less

Repository review

50K input + 3K output tokens

R1 0528$0.032Fits in one request
Kimi K2.7 Code$0.059Fits in one request

R1 0528 costs less

Agent loop

200K input + 10K output tokens

R1 0528$0.122Exceeds the context window
Kimi K2.7 Code$0.230Fits 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 Kimi K2.7 Code
SpecificationDeepSeek R1 0528MoonshotAI Kimi K2.7 Code
MakerDeepSeekMoonshot AI
WeightsOpen weightsOpen weights
ReleasedMay 28, 2025June 12, 2026
Context window164K262K
Input $/Mtok$0.50$0.95
Output $/Mtok$2.18$4.00
Coding indexNot benchmarked53.4
Independent measurements behind it04
Cost per solved taskNot computable$0.35
SourceOpenRouter listingOpenRouter listing

Questions

Is R1 0528 better than Kimi K2.7 Code for coding?

Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; R1 0528 has none, so the two cannot be ranked on coding. Pick R1 0528 for output tokens 1.8x cheaper ($2.18 vs $4.00 per million).

Which is cheaper, R1 0528 or Kimi K2.7 Code?

R1 0528 costs $0.50 per million input tokens and $2.18 per million output tokens; Kimi K2.7 Code costs $0.95 and $4.00. Cost per solved task is known for Kimi K2.7 Code only.

Which has the bigger context window, R1 0528 or Kimi K2.7 Code?

Kimi K2.7 Code, with 262K tokens against 164K.

How many benchmarks is the R1 0528 vs Kimi K2.7 Code comparison based on?

19 benchmarks have a result for both models as of October 22, 2026. R1 0528's coding index rests on 0 independent benchmarks and Kimi K2.7 Code's on 4. Where only one model has a result, the page says so instead of naming a winner.

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