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Gemma 3 4B vs Kimi K2.7 Code

Kimi K2.7 Code leads Gemma 3 4B on the Artificial Analysis Intelligence Index, 25.8 to 4.8, and Gemma 3 4B costs 53.3x less per output token ($0.075 vs $4.00 per million). Updated October 21, 2026; 11 benchmarks have a result for both.

Gemma 3 4BGoogle
Coding
No data
Overall
22.6
Output $/M
$0.075
0
Kimi K2.7 CodeMoonshot AI
Coding
53.4
Overall
56.7
Output $/M
$4.00
11
vs boards won of 11 shared

Gemma 3 4B or Kimi K2.7 Code: which to pick

Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; Gemma 3 4B has none, so the two cannot be ranked on coding.

Pick Gemma 3 4B for output tokens 53.3x cheaper ($0.075 vs $4.00 per million).

Shared results
11
Gemma 3 4B only
31
Kimi K2.7 Code only
40
Like-for-like categories
6 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
Gemma 3 4B not benchmarked, Kimi K2.7 Code 53.4 from 4 benchmarks.
Widest category
Math, 88.1 points apart on average over 1 shared benchmark.
Widest single gap
OTIS Mock AIME: Gemma 3 4B 7.5% against Kimi K2.7 Code 95.6%, 88.1 points apart on a 0 to 100 scale.
Output price
Gemma 3 4B $0.075 against Kimi K2.7 Code $4.00 per million output tokens, 53.3x apart.
Context window
Gemma 3 4B takes 131K 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
CategoryGemma 3 4BBarsKimi K2.7 CodeTies
Coding02
Intelligence02
Agentic work01
Reasoning03
Math01
General02
All shared boards011
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Gemma 3 4B and Kimi K2.7 Code
BenchmarkGemma 3 4BKimi K2.7 CodeLeader
LMArena WebDevNot measured1474Only Kimi K2.7 Code measured
AA Coding Index2.760.8Kimi K2.7 Code
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)11.2%Not measuredOnly Gemma 3 4B measured
SciCodeNot measured47.8%Only Kimi K2.7 Code measured
Terminal-Bench Hard (Artificial Analysis run)0.8%44.7%Kimi K2.7 Code
FrontierCodeNot measured30.1%Only Kimi K2.7 Code measured
WeirdMLNot measured54.1%Only Kimi K2.7 Code measured
ALE-BenchNot measured886.2Only Kimi K2.7 Code measured
LMArena Text: coding1230Not measuredOnly Gemma 3 4B measured
LMArena Text: software and IT1269Not measuredOnly Gemma 3 4B 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
SciCode0.0%Not measuredOnly Gemma 3 4B 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 Gemma 3 4B and Kimi K2.7 Code
BenchmarkGemma 3 4BKimi K2.7 CodeLeader
AA Intelligence Index4.825.8Kimi K2.7 Code
Epoch Capabilities Index115.9150.1Kimi K2.7 Code
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemma 3 4B and Kimi K2.7 Code
BenchmarkGemma 3 4BKimi 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 Telecom5.0%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)19.6%Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for Gemma 3 4B and Kimi K2.7 Code
BenchmarkGemma 3 4BKimi K2.7 CodeLeader
GPQA Diamond (Artificial Analysis run)29.1%89.6%Kimi K2.7 Code
Humanity's Last Exam (Artificial Analysis run)5.3%35.0%Kimi K2.7 Code
GPQA Diamond (Epoch AI run)23.2%87.9%Kimi K2.7 Code
SimpleBenchNot measured57.9%Only Kimi K2.7 Code measured
Chess puzzlesNot measured14.0%Only Kimi K2.7 Code measured
LMArena Text: hard prompts1253Not measuredOnly Gemma 3 4B measured
LMArena Text: expert1223Not measuredOnly Gemma 3 4B measured
LMArena Text: hard prompts in English1253Not measuredOnly Gemma 3 4B measured
Kagi LLM Benchmark25.2%Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index01
Math benchmarks for Gemma 3 4B and Kimi K2.7 Code
BenchmarkGemma 3 4BKimi K2.7 CodeLeader
AA Math Index12.7Not measuredOnly Gemma 3 4B measured
AIME 2025 (Artificial Analysis run)12.7%Not measuredOnly Gemma 3 4B measured
OTIS Mock AIME7.5%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
LMArena Text: math1239Not measuredOnly Gemma 3 4B measured
LMArena Text: mathematical work1256Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 6 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Knowledge benchmarks for Gemma 3 4B and Kimi K2.7 Code
BenchmarkGemma 3 4BKimi K2.7 CodeLeader
MMLU Pro (Artificial Analysis run)41.7%Not measuredOnly Gemma 3 4B measured
SimpleQA VerifiedNot measured36.5%Only Kimi K2.7 Code measured
LMArena Text: science1306Not measuredOnly Gemma 3 4B measured
LMArena Text: medicine and healthcare1342Not measuredOnly Gemma 3 4B measured
LMArena Text: legal and government1327Not measuredOnly Gemma 3 4B measured
LMArena Text: business and finance1311Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Gemma 3 4B and Kimi K2.7 Code
BenchmarkGemma 3 4BKimi K2.7 CodeLeader
Design Arena: websitesNot measured1264Only Kimi K2.7 Code measured
Design Arena: UI componentsNot measured1259Only Kimi K2.7 Code measured
Design Arena: game devNot measured1220Only Kimi K2.7 Code measured
Design Arena: data vizNot measured1227Only Kimi K2.7 Code measured
Design Arena: 3DNot measured1241Only Kimi K2.7 Code measured
Design Arena: all code categoriesNot measured1253Only Kimi K2.7 Code measured
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 Gemma 3 4B and Kimi K2.7 Code
BenchmarkGemma 3 4BKimi K2.7 CodeLeader
IFBench28.3%63.1%Kimi K2.7 Code
Long context reasoning (AA-LCR)6.7%79.3%Kimi K2.7 Code
DTBench50.9%Not measuredOnly Gemma 3 4B measured
LMCA2.8%Not measuredOnly Gemma 3 4B measured
Surface Evolver BenchNot measured48.8%Only Kimi K2.7 Code measured
LMArena Text1291Not measuredOnly Gemma 3 4B measured
LMArena Text: instruction following1239Not measuredOnly Gemma 3 4B measured
LMArena Text: creative writing1270Not measuredOnly Gemma 3 4B measured
LMArena Text: English1300Not measuredOnly Gemma 3 4B measured
LMArena Text: non-English1273Not measuredOnly Gemma 3 4B measured
LMArena Text: German1281Not measuredOnly Gemma 3 4B measured
LMArena Text: Russian1294Not measuredOnly Gemma 3 4B measured
LMArena Text: multi-turn1255Not measuredOnly Gemma 3 4B measured
LMArena Text: longer queries1273Not measuredOnly Gemma 3 4B measured
LMArena Text: writing and language1288Not measuredOnly Gemma 3 4B measured
LMArena Text: entertainment and media1233Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 30 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemma 3 4B and Kimi K2.7 Code
BenchmarkGemma 3 4BKimi 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

Gemma 3 4B$0.0001Fits in one request
Kimi K2.7 Code$0.0029Fits in one request

Gemma 3 4B costs less

Repository review

50K input + 3K output tokens

Gemma 3 4B$0.0025Fits in one request
Kimi K2.7 Code$0.059Fits in one request

Gemma 3 4B costs less

Agent loop

200K input + 10K output tokens

Gemma 3 4B$0.0097Exceeds the context window
Kimi K2.7 Code$0.230Fits in one request

Gemma 3 4B 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 Gemma 3 4B and Kimi K2.7 Code
SpecificationGoogle Gemma 3 4BMoonshotAI Kimi K2.7 Code
MakerGoogleMoonshot AI
WeightsOpen weightsOpen weights
ReleasedMarch 13, 2025June 12, 2026
Context window131K262K
Input $/Mtok$0.045$0.95
Output $/Mtok$0.075$4.00
Coding indexNot benchmarked53.4
Independent measurements behind it04
Cost per solved taskNot computable$0.35
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 3 4B better than Kimi K2.7 Code for coding?

Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; Gemma 3 4B has none, so the two cannot be ranked on coding. Pick Gemma 3 4B for output tokens 53.3x cheaper ($0.075 vs $4.00 per million).

Which is cheaper, Gemma 3 4B or Kimi K2.7 Code?

Gemma 3 4B costs $0.045 per million input tokens and $0.075 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, Gemma 3 4B or Kimi K2.7 Code?

Kimi K2.7 Code, with 262K tokens against 131K.

How many benchmarks is the Gemma 3 4B vs Kimi K2.7 Code comparison based on?

11 benchmarks have a result for both models as of October 21, 2026. Gemma 3 4B'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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