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Gemini 3.7 Flash vs Kimi K2.7 Code

Updated October 21, 2026. 41 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Gemini 3.7 Flash Replace Kimi K2.7 Code
Gemini 3.7 FlashGoogle
Coding
69.9
Overall
39.6
Output $/M
$3.75
40
Kimi K2.7 CodeMoonshot AI
Coding
39.1
Overall
25.8
Output $/M
$3.35
0
vs boards won of 41 shared, 1 tied

Decision reading

Pick Gemini 3.7 Flash for coding: it scores 69.9 on the Vibe Coding Index against 39.1 for Kimi K2.7 Code.

Pick Kimi K2.7 Code when output tokens cost 1.1x less, or when a solved task costs $0.35 against $1.78.

Model AGemini 3.7 FlashGoogle69.9/1002 independent benchmarks$1.78 per solved taskModel BKimi K2.7 CodeMoonshot AI39.1/1001 independent benchmark$0.35 per solved task
Shared results
41
Gemini 3.7 Flash only
71
Kimi K2.7 Code only
10
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
Gemini 3.7 Flash 69.9 from 2 benchmarks, Kimi K2.7 Code 39.1 from 1 benchmark.
Widest category
Knowledge, 32.7 points apart on average over 1 shared benchmark.
Widest single gap
Chess puzzles: Gemini 3.7 Flash 66.0% against Kimi K2.7 Code 14.0%, 52.0 points apart on a 0 to 100 scale.
Output price
Gemini 3.7 Flash $3.75 against Kimi K2.7 Code $3.35 per million output tokens, 1.1x apart.
Context window
Gemini 3.7 Flash 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
CategoryGemini 3.7 FlashBarsKimi K2.7 CodeTies
Coding1401 tie
Intelligence20
Agentic work70
Reasoning40
Math30
Knowledge10
Web design80
General10
All shared boards4001 tie
CodingLike-for-likeFour of these boards feed the Vibe Coding Index140
Coding benchmarks for Gemini 3.7 Flash and Kimi K2.7 Code
BenchmarkGemini 3.7 FlashKimi K2.7 CodeLeader
LiveBench coding80.5%Not measuredOnly Gemini 3.7 Flash measured
LMArena WebDev15911474Gemini 3.7 Flash
AA Coding Index71.560.8Gemini 3.7 Flash
LiveCodeBench (Vals AI)88.7%82.0%Gemini 3.7 Flash
SWE-bench Verified (Vals AI)80.8%78.2%Gemini 3.7 Flash
Terminal-Bench 4 (Vals AI)12.1%Not measuredOnly Gemini 3.7 Flash measured
Vibe Code Bench (Vals AI)70.4%47.2%Gemini 3.7 Flash
Code migration (Vals AI)34.8%25.4%Gemini 3.7 Flash
ProgramBench (Vals AI)0.0%0.0%Tie
IOI (Vals AI)67.8%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench 2.1 (Vals AI)77.5%67.0%Gemini 3.7 Flash
SkillsBench (Vals AI)65.9%50.0%Gemini 3.7 Flash
CyberBench (Vals AI)43.8%Not measuredOnly Gemini 3.7 Flash measured
SciCode59.8%47.8%Gemini 3.7 Flash
Terminal-Bench Hard (Artificial Analysis run)Not measured44.7%Only Kimi K2.7 Code measured
FrontierCode43.6%30.1%Gemini 3.7 Flash
FrontierSWE20.3%Not measuredOnly Gemini 3.7 Flash measured
WeirdMLNot measured54.1%Only Kimi K2.7 Code measured
ALE-Bench904.3886.2Gemini 3.7 Flash
LMArena Text: coding1499Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: software and IT1498Not measuredOnly Gemini 3.7 Flash measured
LMArena WebDev: React15871475Gemini 3.7 Flash
LMArena WebDev: HTML15931451Gemini 3.7 Flash
LMArena WebDev: from an image15991513Gemini 3.7 Flash
Neither model has a result on the other 14 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemini 3.7 Flash and Kimi K2.7 Code
BenchmarkGemini 3.7 FlashKimi K2.7 CodeLeader
AA Intelligence Index39.625.8Gemini 3.7 Flash
Epoch Capabilities Index158.0150.1Gemini 3.7 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index70
Agentic work benchmarks for Gemini 3.7 Flash and Kimi K2.7 Code
BenchmarkGemini 3.7 FlashKimi K2.7 CodeLeader
AA Agentic IndexNot measured21.0Only Kimi K2.7 Code measured
Design Arena: agents building web apps12241176Gemini 3.7 Flash
Design Arena: agents building full-stack apps12081175Gemini 3.7 Flash
Design Arena: agents building mobile apps12301143Gemini 3.7 Flash
Design Arena: agents building Android apps12471143Gemini 3.7 Flash
Design Arena: agents building Godot games12641147Gemini 3.7 Flash
Design Arena: agents building games12351130Gemini 3.7 Flash
Design Arena: HTML slidesNot measured1201Only Kimi K2.7 Code measured
Design Arena: PowerPoint slidesNot measured1154Only Kimi K2.7 Code measured
Design Arena: spreadsheets1028Not measuredOnly Gemini 3.7 Flash measured
LiveBench research76.5%Not measuredOnly Gemini 3.7 Flash measured
LiveBench browser56.0%Not measuredOnly Gemini 3.7 Flash measured
LiveBench long agentic28.3%Not measuredOnly Gemini 3.7 Flash measured
SREBench (Vals AI)4.6%Not measuredOnly Gemini 3.7 Flash measured
Finance Agent (Vals AI)59.0%Not measuredOnly Gemini 3.7 Flash measured
Tax Agent Bench (Vals AI)22.8%Not measuredOnly Gemini 3.7 Flash measured
Legal Research Bench (Vals AI)34.6%Not measuredOnly Gemini 3.7 Flash measured
Excel Modeling Benchmark (Vals AI)71.3%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench-Science (Vals AI)7.1%Not measuredOnly Gemini 3.7 Flash measured
τ²-Bench TelecomNot measured90.1%Only Kimi K2.7 Code measured
APEX-Agents67.8%37.6%Gemini 3.7 Flash
Remote Labor Index5.0%Not measuredOnly Gemini 3.7 Flash measured
Vending-Bench 2Not measured$5,083Only Kimi K2.7 Code measured
Neither model has a result on the other 16 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
Reasoning benchmarks for Gemini 3.7 Flash and Kimi K2.7 Code
BenchmarkGemini 3.7 FlashKimi K2.7 CodeLeader
GPQA Diamond93.9%Not measuredOnly Gemini 3.7 Flash measured
LiveBench reasoning87.8%Not measuredOnly Gemini 3.7 Flash measured
MMMU Pro (Vals AI)89.0%Not measuredOnly Gemini 3.7 Flash measured
GPQA Diamond (Artificial Analysis run)94.5%89.6%Gemini 3.7 Flash
Humanity's Last Exam (Artificial Analysis run)47.9%35.0%Gemini 3.7 Flash
GPQA Diamond (Epoch AI run)94.8%87.9%Gemini 3.7 Flash
ARC-AGI95.5%Not measuredOnly Gemini 3.7 Flash measured
ARC-AGI-284.6%Not measuredOnly Gemini 3.7 Flash measured
SimpleBenchNot measured57.9%Only Kimi K2.7 Code measured
Chess puzzles66.0%14.0%Gemini 3.7 Flash
Mystery game puzzles37.0%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: hard prompts1495Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: expert1512Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: hard prompts in English1487Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: diagrams1329Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: homework1320Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for Gemini 3.7 Flash and Kimi K2.7 Code
BenchmarkGemini 3.7 FlashKimi K2.7 CodeLeader
OTIS Mock AIME97.2%95.6%Gemini 3.7 Flash
FrontierMath, tiers 1 to 371.6%54.0%Gemini 3.7 Flash
FrontierMath, tier 436.6%12.2%Gemini 3.7 Flash
ProofBench58.0%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: math1511Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: mathematical work1502Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for Gemini 3.7 Flash and Kimi K2.7 Code
BenchmarkGemini 3.7 FlashKimi K2.7 CodeLeader
MMLU Pro90.1%Not measuredOnly Gemini 3.7 Flash measured
LegalBench (Vals AI)87.3%Not measuredOnly Gemini 3.7 Flash measured
TaxEval (Vals AI)74.7%Not measuredOnly Gemini 3.7 Flash measured
MortgageTax (Vals AI)66.7%Not measuredOnly Gemini 3.7 Flash measured
MedCode (Vals AI)53.4%Not measuredOnly Gemini 3.7 Flash measured
SimpleQA Verified69.2%36.5%Gemini 3.7 Flash
LMArena Text: science1511Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: medicine and healthcare1494Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: legal and government1496Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: business and finance1479Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for Gemini 3.7 Flash and Kimi K2.7 Code
BenchmarkGemini 3.7 FlashKimi K2.7 CodeLeader
Design Arena: websites13041264Gemini 3.7 Flash
Design Arena: UI components12991259Gemini 3.7 Flash
Design Arena: game dev13181220Gemini 3.7 Flash
Design Arena: data viz13151226Gemini 3.7 Flash
Design Arena: 3D13081241Gemini 3.7 Flash
Design Arena: all code categories13081253Gemini 3.7 Flash
Design Arena: SVG12831176Gemini 3.7 Flash
Design Arena: ASCII art12761196Gemini 3.7 Flash
LiveBench design73.2%Not measuredOnly Gemini 3.7 Flash measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
General benchmarks for Gemini 3.7 Flash and Kimi K2.7 Code
BenchmarkGemini 3.7 FlashKimi K2.7 CodeLeader
LiveBench data analysis68.0%Not measuredOnly Gemini 3.7 Flash measured
SAGE (Vals AI)49.2%Not measuredOnly Gemini 3.7 Flash measured
MedScribe (Vals AI)83.9%Not measuredOnly Gemini 3.7 Flash measured
IFBenchNot measured63.1%Only Kimi K2.7 Code measured
Long context reasoning (AA-LCR)83.0%79.3%Gemini 3.7 Flash
DTBench96.8%Not measuredOnly Gemini 3.7 Flash measured
LMCA50.4%Not measuredOnly Gemini 3.7 Flash measured
Surface Evolver BenchNot measured48.8%Only Kimi K2.7 Code measured
Furniture assembly26.7%Not measuredOnly Gemini 3.7 Flash measured
LMArena Text1489Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: instruction following1484Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: creative writing1488Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision1314Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: English1483Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: non-English1487Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Chinese1552Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: German1506Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Japanese1511Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Korean1481Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: French1500Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Spanish1495Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Russian1515Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: Polish1503Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: multi-turn1485Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: longer queries1492Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: writing and language1491Not measuredOnly Gemini 3.7 Flash measured
LMArena Text: entertainment and media1477Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: English1309Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: Chinese1394Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: reading text1322Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: humor1299Not measuredOnly Gemini 3.7 Flash measured
LMArena Vision: creative writing1312Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 3.7 Flash and Kimi K2.7 Code
BenchmarkGemini 3.7 FlashKimi 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

Gemini 3.7 Flash$0.0026Fits in one request
Kimi K2.7 Code$0.0023Fits in one request

Kimi K2.7 Code costs less

Repository review

50K input + 3K output tokens

Gemini 3.7 Flash$0.049Fits in one request
Kimi K2.7 Code$0.044Fits in one request

Kimi K2.7 Code costs less

Agent loop

200K input + 10K output tokens

Gemini 3.7 Flash$0.188Fits in one request
Kimi K2.7 Code$0.168Fits 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 Gemini 3.7 Flash and Kimi K2.7 Code
SpecificationGoogle Gemini 3.7 FlashMoonshotAI Kimi K2.7 Code
MakerGoogleMoonshot AI
WeightsNo public weights listedOpen weights
ReleasedAugust 13, 2026June 12, 2026
Context window1.05M262K
Input $/Mtok$0.75$0.6712
Output $/Mtok$3.75$3.35
Coding index69.939.1
Independent measurements behind it21
Cost per solved task$1.78$0.35
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.7 Flash better than Kimi K2.7 Code for coding?

Pick Gemini 3.7 Flash for coding: it scores 69.9 on the Vibe Coding Index against 39.1 for Kimi K2.7 Code. Pick Kimi K2.7 Code when output tokens cost 1.1x less, or when a solved task costs $0.35 against $1.78.

Which is cheaper, Gemini 3.7 Flash or Kimi K2.7 Code?

Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; Kimi K2.7 Code costs $0.6712 and $3.35. Per solved SWE-bench Verified task, Gemini 3.7 Flash costs $1.78 and Kimi K2.7 Code $0.35.

Which has the bigger context window, Gemini 3.7 Flash or Kimi K2.7 Code?

Gemini 3.7 Flash, with 1.05M tokens against 262K.

How many benchmarks is the Gemini 3.7 Flash vs Kimi K2.7 Code comparison based on?

41 benchmarks have a result for both models as of October 21, 2026. Gemini 3.7 Flash's coding index rests on 2 independent benchmarks and Kimi K2.7 Code's on 1. Where only one model has a result, the page says so instead of naming a winner.

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