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GPT-5 vs Kimi K2.7 Code

Kimi K2.7 Code leads GPT-5 on coding, 53.4 to 38.8 on the Vibe Coding Index, and Kimi K2.7 Code costs 2.5x less per output token ($4.00 vs $10.00 per million). Updated October 22, 2026; 31 benchmarks have a result for both.

Replace GPT-5 Replace Kimi K2.7 Code
GPT-5OpenAI
Coding
38.8
Overall
51.5
Output $/M
$10.00
8
Kimi K2.7 CodeMoonshot AI
Coding
53.4
Overall
56.7
Output $/M
$4.00
23
vs boards won of 31 shared

GPT-5 or Kimi K2.7 Code: which to pick

Pick Kimi K2.7 Code for coding: it scores 53.4 on the Vibe Coding Index against 38.8 for GPT-5.

Pick GPT-5 for a larger context window (400K against 262K tokens) and work measured by LiveCodeBench (Vals AI) or WeirdML, where it leads.

Model AGPT-5OpenAI38.8/1003 independent benchmarks$0.39 per solved taskModel BKimi K2.7 CodeMoonshot AI53.4/1004 independent benchmarks$0.35 per solved task
Shared results
31
GPT-5 only
82
Kimi K2.7 Code only
20
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
GPT-5 38.8 from 3 benchmarks, Kimi K2.7 Code 53.4 from 4 benchmarks.
Widest category
Knowledge, 13.6 points apart on average over 1 shared benchmark.
Widest single gap
Vibe Code Bench (Vals AI): GPT-5 20.1% against Kimi K2.7 Code 47.2%, 27.1 points apart on a 0 to 100 scale.
Output price
GPT-5 $10.00 against Kimi K2.7 Code $4.00 per million output tokens, 2.5x apart.
Context window
GPT-5 takes 400K 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
CategoryGPT-5BarsKimi K2.7 CodeTies
Coding27
Intelligence02
Agentic work01
Reasoning14
Math21
Knowledge10
Web design17
General11
All shared boards823
CodingLike-for-likeSix of these boards feed the Vibe Coding Index27
Coding benchmarks for GPT-5 and Kimi K2.7 Code
BenchmarkGPT-5Kimi K2.7 CodeLeader
Aider polyglot88.0%Not measuredOnly GPT-5 measured
SWE-bench Verified74.4%Not measuredOnly GPT-5 measured
LMArena WebDev14181474Kimi K2.7 Code
AA Coding Index37.860.8Kimi K2.7 Code
LiveCodeBench (Vals AI)85.9%82.0%GPT-5
SWE-bench Verified (Vals AI)69.0%78.2%Kimi K2.7 Code
Vibe Code Bench (Vals AI)20.1%47.2%Kimi K2.7 Code
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)84.6%Not measuredOnly GPT-5 measured
SciCodeNot measured47.8%Only Kimi K2.7 Code measured
Terminal-Bench Hard (Artificial Analysis run)37.9%44.7%Kimi K2.7 Code
Terminal-Bench49.6%Not measuredOnly GPT-5 measured
FrontierCodeNot measured30.1%Only Kimi K2.7 Code measured
GSO-Bench6.9%Not measuredOnly GPT-5 measured
WeirdML60.7%54.1%GPT-5
ALE-Bench807.6886.2Kimi K2.7 Code
LMArena Text: coding1436Not measuredOnly GPT-5 measured
LMArena Text: software and IT1420Not measuredOnly GPT-5 measured
LMArena WebDev: ReactNot measured1475Only Kimi K2.7 Code measured
LMArena WebDev: HTML14271451Kimi K2.7 Code
LMArena WebDev: from an imageNot measured1513Only Kimi K2.7 Code measured
SciCode0.0%Not measuredOnly GPT-5 measured
Neither model has a result on the other 14 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-5 and Kimi K2.7 Code
BenchmarkGPT-5Kimi K2.7 CodeLeader
AA Intelligence Index23.025.8Kimi K2.7 Code
Epoch Capabilities Index150.0150.1Kimi K2.7 Code
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-5 and Kimi K2.7 Code
BenchmarkGPT-5Kimi 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 Telecom86.5%90.1%Kimi K2.7 Code
APEX-AgentsNot measured37.6%Only Kimi K2.7 Code measured
METR time horizons69.6%Not measuredOnly GPT-5 measured
Remote Labor Index1.7%Not measuredOnly GPT-5 measured
GDPval34.8%Not measuredOnly GPT-5 measured
BALROG32.8%Not measuredOnly GPT-5 measured
DeepResearch Bench49.6%Not measuredOnly GPT-5 measured
Vending-Bench 2Not measured$5,083Only Kimi K2.7 Code measured
BrowseComp-Plus80.0%Not measuredOnly GPT-5 measured
Neither model has a result on the other 23 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index14
Reasoning benchmarks for GPT-5 and Kimi K2.7 Code
BenchmarkGPT-5Kimi K2.7 CodeLeader
GPQA Diamond85.6%Not measuredOnly GPT-5 measured
MMMU Pro (Vals AI)81.5%Not measuredOnly GPT-5 measured
GPQA Diamond (Artificial Analysis run)85.4%89.6%Kimi K2.7 Code
Humanity's Last Exam (Artificial Analysis run)28.5%35.0%Kimi K2.7 Code
GPQA Diamond (Epoch AI run)86.2%87.9%Kimi K2.7 Code
ARC-AGI65.7%Not measuredOnly GPT-5 measured
ARC-AGI-29.9%Not measuredOnly GPT-5 measured
SimpleBench56.7%57.9%Kimi K2.7 Code
Chess puzzles36.0%14.0%GPT-5
Mystery game puzzles23.0%Not measuredOnly GPT-5 measured
EBR-bench12.7%Not measuredOnly GPT-5 measured
VPCT66.0%Not measuredOnly GPT-5 measured
LMArena Text: hard prompts1415Not measuredOnly GPT-5 measured
LMArena Text: expert1419Not measuredOnly GPT-5 measured
LMArena Text: hard prompts in English1419Not measuredOnly GPT-5 measured
LMArena Vision: diagrams1252Not measuredOnly GPT-5 measured
LMArena Vision: homework1278Not measuredOnly GPT-5 measured
Kagi LLM Benchmark72.7%Not measuredOnly GPT-5 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index21
Math benchmarks for GPT-5 and Kimi K2.7 Code
BenchmarkGPT-5Kimi K2.7 CodeLeader
AIME93.4%Not measuredOnly GPT-5 measured
MATH 500 (Vals AI)96.0%Not measuredOnly GPT-5 measured
MGSM (Vals AI)92.8%Not measuredOnly GPT-5 measured
AA Math Index94.3Not measuredOnly GPT-5 measured
AIME 2025 (Artificial Analysis run)94.3%Not measuredOnly GPT-5 measured
OTIS Mock AIME91.4%95.6%Kimi K2.7 Code
FrontierMath, tiers 1 to 355.4%54.0%GPT-5
FrontierMath, tier 422.0%12.2%GPT-5
ProofBench18.0%Not measuredOnly GPT-5 measured
MATH level 598.1%Not measuredOnly GPT-5 measured
LMArena Text: math1407Not measuredOnly GPT-5 measured
LMArena Text: mathematical work1405Not measuredOnly GPT-5 measured
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for GPT-5 and Kimi K2.7 Code
BenchmarkGPT-5Kimi K2.7 CodeLeader
MMLU Pro86.5%Not measuredOnly GPT-5 measured
LegalBench (Vals AI)86.0%Not measuredOnly GPT-5 measured
CaseLaw (Vals AI)66.5%Not measuredOnly GPT-5 measured
CorpFin (Vals AI)61.1%Not measuredOnly GPT-5 measured
TaxEval (Vals AI)73.4%Not measuredOnly GPT-5 measured
MortgageTax (Vals AI)65.5%Not measuredOnly GPT-5 measured
MedQA (Vals AI)96.3%Not measuredOnly GPT-5 measured
MedCode (Vals AI)49.6%Not measuredOnly GPT-5 measured
MMLU Pro (Artificial Analysis run)87.1%Not measuredOnly GPT-5 measured
SimpleQA Verified50.1%36.5%GPT-5
GeoBench81.0%Not measuredOnly GPT-5 measured
LMArena Text: science1416Not measuredOnly GPT-5 measured
LMArena Text: medicine and healthcare1413Not measuredOnly GPT-5 measured
LMArena Text: legal and government1431Not measuredOnly GPT-5 measured
LMArena Text: business and finance1400Not measuredOnly GPT-5 measured
FACTS Benchmark Suite56.5%Not measuredOnly GPT-5 measured
Neither model has a result on the other 2 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index17
Web design benchmarks for GPT-5 and Kimi K2.7 Code
BenchmarkGPT-5Kimi K2.7 CodeLeader
Design Arena: websites11841263Kimi K2.7 Code
Design Arena: UI components11771255Kimi K2.7 Code
Design Arena: game dev11851220Kimi K2.7 Code
Design Arena: data viz12211227Kimi K2.7 Code
Design Arena: 3D10551240Kimi K2.7 Code
Design Arena: all code categories11671252Kimi K2.7 Code
Design Arena: SVG11881176GPT-5
Design Arena: ASCII art11411196Kimi K2.7 Code
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
General benchmarks for GPT-5 and Kimi K2.7 Code
BenchmarkGPT-5Kimi K2.7 CodeLeader
SAGE (Vals AI)43.7%Not measuredOnly GPT-5 measured
MedScribe (Vals AI)83.7%Not measuredOnly GPT-5 measured
IFBench73.1%63.1%GPT-5
Long context reasoning (AA-LCR)78.2%79.3%Kimi K2.7 Code
DTBench90.7%Not measuredOnly GPT-5 measured
LMCA40.0%Not measuredOnly GPT-5 measured
Fiction.LiveBench97.2%Not measuredOnly GPT-5 measured
Creative writing (Lech Mazur)86.0%Not measuredOnly GPT-5 measured
Surface Evolver BenchNot measured48.8%Only Kimi K2.7 Code measured
LMArena Text1406Not measuredOnly GPT-5 measured
LMArena Text: instruction following1388Not measuredOnly GPT-5 measured
LMArena Text: creative writing1365Not measuredOnly GPT-5 measured
LMArena Vision1232Not measuredOnly GPT-5 measured
LMArena Text: English1409Not measuredOnly GPT-5 measured
LMArena Text: non-English1397Not measuredOnly GPT-5 measured
LMArena Text: Chinese1422Not measuredOnly GPT-5 measured
LMArena Text: German1416Not measuredOnly GPT-5 measured
LMArena Text: Japanese1409Not measuredOnly GPT-5 measured
LMArena Text: Korean1360Not measuredOnly GPT-5 measured
LMArena Text: French1409Not measuredOnly GPT-5 measured
LMArena Text: Spanish1399Not measuredOnly GPT-5 measured
LMArena Text: Russian1407Not measuredOnly GPT-5 measured
LMArena Text: Polish1431Not measuredOnly GPT-5 measured
LMArena Text: multi-turn1426Not measuredOnly GPT-5 measured
LMArena Text: longer queries1399Not measuredOnly GPT-5 measured
LMArena Text: writing and language1384Not measuredOnly GPT-5 measured
LMArena Text: entertainment and media1379Not measuredOnly GPT-5 measured
LMArena Vision: English1231Not measuredOnly GPT-5 measured
LMArena Vision: Chinese1267Not measuredOnly GPT-5 measured
LMArena Vision: reading text1246Not measuredOnly GPT-5 measured
LMArena Vision: humor1219Not measuredOnly GPT-5 measured
LMArena Vision: captioning1212Not measuredOnly GPT-5 measured
LMArena Vision: recognizing things1263Not measuredOnly GPT-5 measured
LMArena Vision: creative writing1210Not measuredOnly GPT-5 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 GPT-5 and Kimi K2.7 Code
BenchmarkGPT-5Kimi 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

GPT-5$0.0063Fits in one request
Kimi K2.7 Code$0.0029Fits in one request

Kimi K2.7 Code costs less

Repository review

50K input + 3K output tokens

GPT-5$0.092Fits in one request
Kimi K2.7 Code$0.059Fits in one request

Kimi K2.7 Code costs less

Agent loop

200K input + 10K output tokens

GPT-5$0.350Fits in one request
Kimi K2.7 Code$0.230Fits in one request

Kimi K2.7 Code 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 GPT-5 and Kimi K2.7 Code
SpecificationOpenAI GPT-5MoonshotAI Kimi K2.7 Code
MakerOpenAIMoonshot AI
WeightsNo public weights listedOpen weights
ReleasedAugust 7, 2025June 12, 2026
Context window400K262K
Input $/Mtok$1.25$0.95
Output $/Mtok$10.00$4.00
Coding index38.853.4
Independent measurements behind it34
Cost per solved task$0.39$0.35
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5 better than Kimi K2.7 Code for coding?

Pick Kimi K2.7 Code for coding: it scores 53.4 on the Vibe Coding Index against 38.8 for GPT-5. Pick GPT-5 for a larger context window (400K against 262K tokens) and work measured by LiveCodeBench (Vals AI) or WeirdML, where it leads.

Which is cheaper, GPT-5 or Kimi K2.7 Code?

GPT-5 costs $1.25 per million input tokens and $10.00 per million output tokens; Kimi K2.7 Code costs $0.95 and $4.00. Per solved SWE-bench Verified task, GPT-5 costs $0.39 and Kimi K2.7 Code $0.35.

Which has the bigger context window, GPT-5 or Kimi K2.7 Code?

GPT-5, with 400K tokens against 262K.

How many benchmarks is the GPT-5 vs Kimi K2.7 Code comparison based on?

31 benchmarks have a result for both models as of October 22, 2026. GPT-5's coding index rests on 3 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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