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Gemma 3 4B vs Kimi K2 0711

Updated October 21, 2026. 12 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Gemma 3 4BGoogle
Coding
No data
Overall
4.8
Output $/M
$0.075
0
Kimi K2 0711Moonshot AI
Coding
No data
Overall
12.7
Output $/M
$2.30
12
vs boards won of 12 shared

Decision reading

Neither model has a coding score yet, so the two cannot be ranked on coding.

Gemma 3 4B has the edge where output tokens cost 30.7x less, and where what matters is LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Shared results
12
Gemma 3 4B only
27
Kimi K2 0711 only
24
Like-for-like categories
7 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
Gemma 3 4B not benchmarked, Kimi K2 0711 not benchmarked.
Widest category
Agentic work, 56.1 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Gemma 3 4B 5.0% against Kimi K2 0711 61.1%, 56.1 points apart on a 0 to 100 scale.
Output price
Gemma 3 4B $0.075 against Kimi K2 0711 $2.30 per million output tokens, 30.7x apart.
Context window
Both take 131K tokens.

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 0711Ties
Coding02
Intelligence02
Agentic work01
Reasoning02
Math02
Knowledge01
General02
All shared boards012
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Gemma 3 4B and Kimi K2 0711
BenchmarkGemma 3 4BKimi K2 0711Leader
Aider polyglotNot measured59.1%Only Kimi K2 0711 measured
SWE-bench VerifiedNot measured71.2%Only Kimi K2 0711 measured
AA Coding Index2.7Not measuredOnly Gemma 3 4B measured
LiveCodeBench (Vals AI)Not measured70.5%Only Kimi K2 0711 measured
LiveCodeBench (Artificial Analysis run)11.2%55.6%Kimi K2 0711
Terminal-Bench Hard (Artificial Analysis run)0.8%15.9%Kimi K2 0711
Terminal-BenchNot measured27.8%Only Kimi K2 0711 measured
GSO-BenchNot measured4.9%Only Kimi K2 0711 measured
WeirdMLNot measured39.4%Only Kimi K2 0711 measured
LMArena Text: coding1230Not measuredOnly Gemma 3 4B measured
LMArena Text: software and IT1269Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemma 3 4B and Kimi K2 0711
BenchmarkGemma 3 4BKimi K2 0711Leader
AA Intelligence Index4.812.7Kimi K2 0711
Epoch Capabilities Index115.9140.0Kimi K2 0711
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemma 3 4B and Kimi K2 0711
BenchmarkGemma 3 4BKimi K2 0711Leader
τ²-Bench Telecom5.0%61.1%Kimi K2 0711
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for Gemma 3 4B and Kimi K2 0711
BenchmarkGemma 3 4BKimi K2 0711Leader
GPQA DiamondNot measured71.5%Only Kimi K2 0711 measured
GPQA Diamond (Artificial Analysis run)29.1%76.6%Kimi K2 0711
Humanity's Last Exam (Artificial Analysis run)5.3%7.4%Kimi K2 0711
GPQA Diamond (Epoch AI run)23.2%Not measuredOnly Gemma 3 4B measured
SimpleBenchNot measured26.3%Only Kimi K2 0711 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
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Gemma 3 4B and Kimi K2 0711
BenchmarkGemma 3 4BKimi K2 0711Leader
AIMENot measured62.7%Only Kimi K2 0711 measured
MATH 500 (Vals AI)Not measured94.2%Only Kimi K2 0711 measured
MGSM (Vals AI)Not measured91.0%Only Kimi K2 0711 measured
AA Math Index12.757.0Kimi K2 0711
AIME 2025 (Artificial Analysis run)12.7%57.0%Kimi K2 0711
OTIS Mock AIME7.5%Not measuredOnly Gemma 3 4B 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 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
Knowledge benchmarks for Gemma 3 4B and Kimi K2 0711
BenchmarkGemma 3 4BKimi K2 0711Leader
MMLU ProNot measured79.4%Only Kimi K2 0711 measured
LegalBench (Vals AI)Not measured81.5%Only Kimi K2 0711 measured
CorpFin (Vals AI)Not measured50.4%Only Kimi K2 0711 measured
TaxEval (Vals AI)Not measured70.2%Only Kimi K2 0711 measured
MedQA (Vals AI)Not measured84.0%Only Kimi K2 0711 measured
MMLU Pro (Artificial Analysis run)41.7%82.4%Kimi K2 0711
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 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Web design benchmarks for Gemma 3 4B and Kimi K2 0711
BenchmarkGemma 3 4BKimi K2 0711Leader
Design Arena: websitesNot measured1050Only Kimi K2 0711 measured
Design Arena: UI componentsNot measured1030Only Kimi K2 0711 measured
Design Arena: game devNot measured974Only Kimi K2 0711 measured
Design Arena: data vizNot measured1018Only Kimi K2 0711 measured
Design Arena: all code categoriesNot measured1033Only Kimi K2 0711 measured
Neither model has a result on the other 4 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
General benchmarks for Gemma 3 4B and Kimi K2 0711
BenchmarkGemma 3 4BKimi K2 0711Leader
IFBench28.3%41.5%Kimi K2 0711
Long context reasoning (AA-LCR)6.7%53.0%Kimi K2 0711
DTBench50.9%Not measuredOnly Gemma 3 4B measured
LMCA2.8%Not measuredOnly Gemma 3 4B measured
Fiction.LiveBenchNot measured61.1%Only Kimi K2 0711 measured
Creative writing (Lech Mazur)Not measured85.6%Only Kimi K2 0711 measured
CL-benchNot measured11.9%Only Kimi K2 0711 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 28 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 0711
BenchmarkGemma 3 4BKimi K2 0711Leader
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 0711$0.0017Fits 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 0711$0.035Fits 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 0711$0.137Exceeds the context window

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 0711
SpecificationGoogle Gemma 3 4BMoonshotAI Kimi K2 0711
MakerGoogleMoonshot AI
WeightsOpen weightsOpen weights
ReleasedMarch 13, 2025July 11, 2025
Context window131K131K
Input $/Mtok$0.045$0.57
Output $/Mtok$0.075$2.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 3 4B better than Kimi K2 0711 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Gemma 3 4B has the edge where output tokens cost 30.7x less, and where what matters is LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Which is cheaper, Gemma 3 4B or Kimi K2 0711?

Gemma 3 4B costs $0.045 per million input tokens and $0.075 per million output tokens; Kimi K2 0711 costs $0.57 and $2.30. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemma 3 4B or Kimi K2 0711?

Neither: both take 131K tokens.

How many benchmarks is the Gemma 3 4B vs Kimi K2 0711 comparison based on?

12 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 0711's on 0. Where only one model has a result, the page says so instead of naming a winner.

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