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GPT-4.1 Nano vs Kimi K2.7 Code

Kimi K2.7 Code leads GPT-4.1 Nano on the Artificial Analysis Intelligence Index, 25.8 to 7.8, and GPT-4.1 Nano costs 10.0x less per output token ($0.40 vs $4.00 per million). Updated October 21, 2026; 21 benchmarks have a result for both.

Replace GPT-4.1 Nano Replace Kimi K2.7 Code
GPT-4.1 NanoOpenAI
Coding
No data
Overall
24.7
Output $/M
$0.40
0
Kimi K2.7 CodeMoonshot AI
Coding
53.4
Overall
56.7
Output $/M
$4.00
21
vs boards won of 21 shared

GPT-4.1 Nano or Kimi K2.7 Code: which to pick

Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; GPT-4.1 Nano has none, so the two cannot be ranked on coding.

Pick GPT-4.1 Nano for output tokens 10.0x cheaper ($0.40 vs $4.00 per million) and a larger context window (1.05M against 262K tokens).

Model AGPT-4.1 NanoOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BKimi K2.7 CodeMoonshot AI53.4/1004 independent benchmarks$0.35 per solved task
Shared results
21
GPT-4.1 Nano only
50
Kimi K2.7 Code only
30
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-4.1 Nano not benchmarked, Kimi K2.7 Code 53.4 from 4 benchmarks.
Widest category
Agentic work, 72.8 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GPT-4.1 Nano 17.3% against Kimi K2.7 Code 90.1%, 72.8 points apart on a 0 to 100 scale.
Output price
GPT-4.1 Nano $0.40 against Kimi K2.7 Code $4.00 per million output tokens, 10.0x apart.
Context window
GPT-4.1 Nano takes 1.05M 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-4.1 NanoBarsKimi K2.7 CodeTies
Coding04
Intelligence02
Agentic work01
Reasoning04
Math01
Knowledge01
Web design06
General02
All shared boards021
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for GPT-4.1 Nano and Kimi K2.7 Code
BenchmarkGPT-4.1 NanoKimi K2.7 CodeLeader
Aider polyglot8.9%Not measuredOnly GPT-4.1 Nano measured
LMArena WebDevNot measured1474Only Kimi K2.7 Code measured
AA Coding Index11.160.8Kimi K2.7 Code
LiveCodeBench (Vals AI)42.7%82.0%Kimi K2.7 Code
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)32.6%Not measuredOnly GPT-4.1 Nano measured
SciCodeNot measured47.8%Only Kimi K2.7 Code measured
Terminal-Bench Hard (Artificial Analysis run)3.8%44.7%Kimi K2.7 Code
FrontierCodeNot measured30.1%Only Kimi K2.7 Code measured
WeirdML19.0%54.1%Kimi K2.7 Code
ALE-BenchNot measured886.2Only Kimi K2.7 Code measured
LMArena Text: coding1306Not measuredOnly GPT-4.1 Nano measured
LMArena Text: software and IT1305Not measuredOnly GPT-4.1 Nano 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 index02
Intelligence benchmarks for GPT-4.1 Nano and Kimi K2.7 Code
BenchmarkGPT-4.1 NanoKimi K2.7 CodeLeader
AA Intelligence Index7.825.8Kimi K2.7 Code
Epoch Capabilities Index129.5150.1Kimi K2.7 Code
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-4.1 Nano and Kimi K2.7 Code
BenchmarkGPT-4.1 NanoKimi 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 measured1137Only Kimi K2.7 Code measured
Design Arena: agents building Godot gamesNot measured1147Only Kimi K2.7 Code measured
Design Arena: agents building gamesNot measured1131Only Kimi K2.7 Code measured
Design Arena: HTML slidesNot measured1201Only Kimi K2.7 Code measured
Design Arena: PowerPoint slidesNot measured1154Only Kimi K2.7 Code measured
τ²-Bench Telecom17.3%90.1%Kimi K2.7 Code
APEX-AgentsNot measured37.6%Only Kimi K2.7 Code measured
Vending-Bench 2Not measured$5,083Only Kimi K2.7 Code measured
Berkeley Function Calling Leaderboard (BFCL)33.1%Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for GPT-4.1 Nano and Kimi K2.7 Code
BenchmarkGPT-4.1 NanoKimi K2.7 CodeLeader
GPQA Diamond50.8%Not measuredOnly GPT-4.1 Nano measured
MMMU Pro (Vals AI)55.0%Not measuredOnly GPT-4.1 Nano measured
GPQA Diamond (Artificial Analysis run)51.2%89.6%Kimi K2.7 Code
Humanity's Last Exam (Artificial Analysis run)3.8%35.0%Kimi K2.7 Code
GPQA Diamond (Epoch AI run)48.9%87.9%Kimi K2.7 Code
ARC-AGI0.0%Not measuredOnly GPT-4.1 Nano measured
ARC-AGI-20.0%Not measuredOnly GPT-4.1 Nano measured
SimpleBenchNot measured57.9%Only Kimi K2.7 Code measured
Chess puzzles0.0%14.0%Kimi K2.7 Code
LMArena Text: hard prompts1286Not measuredOnly GPT-4.1 Nano measured
LMArena Text: expert1271Not measuredOnly GPT-4.1 Nano measured
LMArena Text: hard prompts in English1293Not measuredOnly GPT-4.1 Nano measured
Kagi LLM Benchmark33.3%Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index01
Math benchmarks for GPT-4.1 Nano and Kimi K2.7 Code
BenchmarkGPT-4.1 NanoKimi K2.7 CodeLeader
AIME26.5%Not measuredOnly GPT-4.1 Nano measured
MATH 500 (Vals AI)80.2%Not measuredOnly GPT-4.1 Nano measured
MGSM (Vals AI)69.3%Not measuredOnly GPT-4.1 Nano measured
AA Math Index24.0Not measuredOnly GPT-4.1 Nano measured
AIME 2025 (Artificial Analysis run)24.0%Not measuredOnly GPT-4.1 Nano measured
OTIS Mock AIME28.9%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 570.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: math1274Not measuredOnly GPT-4.1 Nano measured
LMArena Text: mathematical work1274Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
Knowledge benchmarks for GPT-4.1 Nano and Kimi K2.7 Code
BenchmarkGPT-4.1 NanoKimi K2.7 CodeLeader
MMLU Pro63.5%Not measuredOnly GPT-4.1 Nano measured
LegalBench (Vals AI)61.1%Not measuredOnly GPT-4.1 Nano measured
CorpFin (Vals AI)42.1%Not measuredOnly GPT-4.1 Nano measured
TaxEval (Vals AI)60.8%Not measuredOnly GPT-4.1 Nano measured
MortgageTax (Vals AI)52.8%Not measuredOnly GPT-4.1 Nano measured
MedQA (Vals AI)68.2%Not measuredOnly GPT-4.1 Nano measured
MMLU Pro (Artificial Analysis run)65.7%Not measuredOnly GPT-4.1 Nano measured
SimpleQA Verified6.0%36.5%Kimi K2.7 Code
LMArena Text: science1297Not measuredOnly GPT-4.1 Nano measured
LMArena Text: medicine and healthcare1276Not measuredOnly GPT-4.1 Nano measured
LMArena Text: legal and government1300Not measuredOnly GPT-4.1 Nano measured
LMArena Text: business and finance1267Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for GPT-4.1 Nano and Kimi K2.7 Code
BenchmarkGPT-4.1 NanoKimi K2.7 CodeLeader
Design Arena: websites9731264Kimi K2.7 Code
Design Arena: UI components9161259Kimi K2.7 Code
Design Arena: game dev9711220Kimi K2.7 Code
Design Arena: data viz8901227Kimi K2.7 Code
Design Arena: 3D9251241Kimi K2.7 Code
Design Arena: all code categories9631253Kimi K2.7 Code
Design Arena: SVGNot measured1176Only Kimi K2.7 Code measured
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 GPT-4.1 Nano and Kimi K2.7 Code
BenchmarkGPT-4.1 NanoKimi K2.7 CodeLeader
IFBench32.0%63.1%Kimi K2.7 Code
Long context reasoning (AA-LCR)20.3%79.3%Kimi K2.7 Code
DTBench52.5%Not measuredOnly GPT-4.1 Nano measured
LMCA5.5%Not measuredOnly GPT-4.1 Nano measured
Fiction.LiveBench25.0%Not measuredOnly GPT-4.1 Nano measured
Surface Evolver BenchNot measured48.8%Only Kimi K2.7 Code measured
LMArena Text1285Not measuredOnly GPT-4.1 Nano measured
LMArena Text: instruction following1266Not measuredOnly GPT-4.1 Nano measured
LMArena Text: creative writing1260Not measuredOnly GPT-4.1 Nano measured
LMArena Vision1063Not measuredOnly GPT-4.1 Nano measured
LMArena Text: English1303Not measuredOnly GPT-4.1 Nano measured
LMArena Text: non-English1260Not measuredOnly GPT-4.1 Nano measured
LMArena Text: Chinese1270Not measuredOnly GPT-4.1 Nano measured
LMArena Text: German1288Not measuredOnly GPT-4.1 Nano measured
LMArena Text: Japanese1198Not measuredOnly GPT-4.1 Nano measured
LMArena Text: Russian1261Not measuredOnly GPT-4.1 Nano measured
LMArena Text: multi-turn1277Not measuredOnly GPT-4.1 Nano measured
LMArena Text: longer queries1283Not measuredOnly GPT-4.1 Nano measured
LMArena Text: writing and language1261Not measuredOnly GPT-4.1 Nano measured
LMArena Text: entertainment and media1243Not measuredOnly GPT-4.1 Nano measured
LMArena Vision: English1101Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 25 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4.1 Nano and Kimi K2.7 Code
BenchmarkGPT-4.1 NanoKimi 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-4.1 Nano$0.0003Fits in one request
Kimi K2.7 Code$0.0029Fits in one request

GPT-4.1 Nano costs less

Repository review

50K input + 3K output tokens

GPT-4.1 Nano$0.0062Fits in one request
Kimi K2.7 Code$0.059Fits in one request

GPT-4.1 Nano costs less

Agent loop

200K input + 10K output tokens

GPT-4.1 Nano$0.024Fits in one request
Kimi K2.7 Code$0.230Fits in one request

GPT-4.1 Nano 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-4.1 Nano and Kimi K2.7 Code
SpecificationOpenAI GPT-4.1 NanoMoonshotAI Kimi K2.7 Code
MakerOpenAIMoonshot AI
WeightsNo public weights listedOpen weights
ReleasedApril 14, 2025June 12, 2026
Context window1.05M262K
Input $/Mtok$0.10$0.95
Output $/Mtok$0.40$4.00
Coding indexNot benchmarked53.4
Independent measurements behind it04
Cost per solved taskNot computable$0.35
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 Nano better than Kimi K2.7 Code for coding?

Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; GPT-4.1 Nano has none, so the two cannot be ranked on coding. Pick GPT-4.1 Nano for output tokens 10.0x cheaper ($0.40 vs $4.00 per million) and a larger context window (1.05M against 262K tokens).

Which is cheaper, GPT-4.1 Nano or Kimi K2.7 Code?

GPT-4.1 Nano costs $0.10 per million input tokens and $0.40 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, GPT-4.1 Nano or Kimi K2.7 Code?

GPT-4.1 Nano, with 1.05M tokens against 262K.

How many benchmarks is the GPT-4.1 Nano vs Kimi K2.7 Code comparison based on?

21 benchmarks have a result for both models as of October 21, 2026. GPT-4.1 Nano'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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