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Gemma 3 4B vs MiniMax M2.7

MiniMax M2.7 leads Gemma 3 4B on the Artificial Analysis Intelligence Index, 22.8 to 4.8, and Gemma 3 4B costs 16.0x less per output token ($0.075 vs $1.20 per million). Updated October 22, 2026; 31 benchmarks have a result for both.

Replace Gemma 3 4B Replace MiniMax M2.7
Gemma 3 4BGoogle
Coding
No data
Overall
22.6
Output $/M
$0.075
0
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
31
vs boards won of 31 shared

Gemma 3 4B or MiniMax M2.7: which to pick

Only MiniMax M2.7 has a coding score, 36.2 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 16.0x cheaper ($0.075 vs $1.20 per million).

Model AGemma 3 4BGoogleNot benchmarkedNo coding benchmarkNo cost per solved taskModel BMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved task
Shared results
31
Gemma 3 4B only
11
MiniMax M2.7 only
43
Like-for-like categories
7 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, MiniMax M2.7 36.2 from 3 benchmarks.
Widest category
Agentic work, 79.8 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Gemma 3 4B 5.0% against MiniMax M2.7 84.8%, 79.8 points apart on a 0 to 100 scale.
Output price
Gemma 3 4B $0.075 against MiniMax M2.7 $1.20 per million output tokens, 16.0x apart.
Context window
Gemma 3 4B takes 131K tokens, MiniMax M2.7 205K.

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 4BBarsMiniMax M2.7Ties
Coding04
Intelligence02
Agentic work01
Reasoning05
Math02
Knowledge04
General013
All shared boards031
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for Gemma 3 4B and MiniMax M2.7
BenchmarkGemma 3 4BMiniMax M2.7Leader
LMArena WebDevNot measured1399Only MiniMax M2.7 measured
AA Coding Index2.752.6MiniMax M2.7
LiveCodeBench (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
SWE-bench Verified (Vals AI)Not measured73.8%Only MiniMax M2.7 measured
Vibe Code Bench (Vals AI)Not measured11.9%Only MiniMax M2.7 measured
Code migration (Vals AI)Not measured8.7%Only MiniMax M2.7 measured
ProgramBench (Vals AI)Not measured0.0%Only MiniMax M2.7 measured
Terminal-Bench 2.1 (Vals AI)Not measured48.7%Only MiniMax M2.7 measured
LiveCodeBench (Artificial Analysis run)11.2%Not measuredOnly Gemma 3 4B measured
SciCodeNot measured50.1%Only MiniMax M2.7 measured
Terminal-Bench Hard (Artificial Analysis run)0.8%39.4%MiniMax M2.7
Terminal-BenchNot measured45.1%Only MiniMax M2.7 measured
WeirdMLNot measured37.0%Only MiniMax M2.7 measured
ALE-BenchNot measured599.3Only MiniMax M2.7 measured
LMArena Text: coding12301454MiniMax M2.7
LMArena Text: software and IT12691446MiniMax M2.7
LMArena WebDev: ReactNot measured1388Only MiniMax M2.7 measured
LMArena WebDev: HTMLNot measured1401Only MiniMax M2.7 measured
SciCode0.0%Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemma 3 4B and MiniMax M2.7
BenchmarkGemma 3 4BMiniMax M2.7Leader
AA Intelligence Index4.822.8MiniMax M2.7
Epoch Capabilities Index115.9145.8MiniMax M2.7
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemma 3 4B and MiniMax M2.7
BenchmarkGemma 3 4BMiniMax M2.7Leader
AA Agentic IndexNot measured15.3Only MiniMax M2.7 measured
Finance Agent (Vals AI)Not measured27.9%Only MiniMax M2.7 measured
Tax Agent Bench (Vals AI)Not measured6.9%Only MiniMax M2.7 measured
Legal Research Bench (Vals AI)Not measured10.6%Only MiniMax M2.7 measured
Excel Modeling Benchmark (Vals AI)Not measured28.4%Only MiniMax M2.7 measured
τ²-Bench Telecom5.0%84.8%MiniMax M2.7
Berkeley Function Calling Leaderboard (BFCL)19.6%Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Gemma 3 4B and MiniMax M2.7
BenchmarkGemma 3 4BMiniMax M2.7Leader
GPQA DiamondNot measured86.6%Only MiniMax M2.7 measured
GPQA Diamond (Artificial Analysis run)29.1%87.4%MiniMax M2.7
Humanity's Last Exam (Artificial Analysis run)5.3%29.6%MiniMax M2.7
GPQA Diamond (Epoch AI run)23.2%Not measuredOnly Gemma 3 4B measured
LMArena Text: hard prompts12531422MiniMax M2.7
LMArena Text: expert12231443MiniMax M2.7
LMArena Text: hard prompts in English12531441MiniMax M2.7
Kagi LLM Benchmark25.2%Not measuredOnly Gemma 3 4B measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Gemma 3 4B and MiniMax M2.7
BenchmarkGemma 3 4BMiniMax M2.7Leader
AIMENot measured91.0%Only MiniMax M2.7 measured
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%Not measuredOnly Gemma 3 4B measured
ProofBenchNot measured3.0%Only MiniMax M2.7 measured
LMArena Text: math12391421MiniMax M2.7
LMArena Text: mathematical work12561437MiniMax M2.7
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Gemma 3 4B and MiniMax M2.7
BenchmarkGemma 3 4BMiniMax M2.7Leader
MMLU ProNot measured80.4%Only MiniMax M2.7 measured
LegalBench (Vals AI)Not measured84.0%Only MiniMax M2.7 measured
CaseLaw (Vals AI)Not measured60.9%Only MiniMax M2.7 measured
CorpFin (Vals AI)Not measured61.2%Only MiniMax M2.7 measured
TaxEval (Vals AI)Not measured66.6%Only MiniMax M2.7 measured
MedCode (Vals AI)Not measured34.4%Only MiniMax M2.7 measured
MMLU Pro (Artificial Analysis run)41.7%Not measuredOnly Gemma 3 4B measured
LMArena Text: science13061416MiniMax M2.7
LMArena Text: medicine and healthcare13421409MiniMax M2.7
LMArena Text: legal and government13271403MiniMax M2.7
LMArena Text: business and finance13111407MiniMax M2.7
Neither model has a result on the other 7 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 MiniMax M2.7
BenchmarkGemma 3 4BMiniMax M2.7Leader
Design Arena: websitesNot measured1243Only MiniMax M2.7 measured
Design Arena: UI componentsNot measured1210Only MiniMax M2.7 measured
Design Arena: game devNot measured1209Only MiniMax M2.7 measured
Design Arena: data vizNot measured1233Only MiniMax M2.7 measured
Design Arena: 3DNot measured1195Only MiniMax M2.7 measured
Design Arena: all code categoriesNot measured1233Only MiniMax M2.7 measured
Design Arena: SVGNot measured1137Only MiniMax M2.7 measured
Design Arena: ASCII artNot measured1136Only MiniMax M2.7 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index013
General benchmarks for Gemma 3 4B and MiniMax M2.7
BenchmarkGemma 3 4BMiniMax M2.7Leader
MedScribe (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
IFBench28.3%75.7%MiniMax M2.7
Long context reasoning (AA-LCR)6.7%78.3%MiniMax M2.7
DTBench50.9%Not measuredOnly Gemma 3 4B measured
LMCA2.8%Not measuredOnly Gemma 3 4B measured
ExploitBenchNot measured13.3%Only MiniMax M2.7 measured
LMArena Text12911405MiniMax M2.7
LMArena Text: instruction following12391405MiniMax M2.7
LMArena Text: creative writing12701354MiniMax M2.7
LMArena Text: English13001426MiniMax M2.7
LMArena Text: non-English12731382MiniMax M2.7
LMArena Text: ChineseNot measured1442Only MiniMax M2.7 measured
LMArena Text: German12811398MiniMax M2.7
LMArena Text: JapaneseNot measured1260Only MiniMax M2.7 measured
LMArena Text: KoreanNot measured1314Only MiniMax M2.7 measured
LMArena Text: FrenchNot measured1424Only MiniMax M2.7 measured
LMArena Text: SpanishNot measured1402Only MiniMax M2.7 measured
LMArena Text: Russian12941383MiniMax M2.7
LMArena Text: PolishNot measured1387Only MiniMax M2.7 measured
LMArena Text: multi-turn12551412MiniMax M2.7
LMArena Text: longer queries12731418MiniMax M2.7
LMArena Text: writing and language12881376MiniMax M2.7
LMArena Text: entertainment and media12331360MiniMax M2.7
Neither model has a result on the other 23 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 MiniMax M2.7
BenchmarkGemma 3 4BMiniMax M2.7Leader
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
MiniMax M2.7$0.0009Fits in one request

Gemma 3 4B costs less

Repository review

50K input + 3K output tokens

Gemma 3 4B$0.0025Fits in one request
MiniMax M2.7$0.019Fits in one request

Gemma 3 4B costs less

Agent loop

200K input + 10K output tokens

Gemma 3 4B$0.0097Exceeds the context window
MiniMax M2.7$0.072Exceeds 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 MiniMax M2.7
SpecificationGoogle Gemma 3 4BMiniMax M2.7
MakerGoogleMiniMax
WeightsOpen weightsOpen weights
ReleasedMarch 13, 2025March 18, 2026
Context window131K205K
Input $/Mtok$0.045$0.30
Output $/Mtok$0.075$1.20
Coding indexNot benchmarked36.2
Independent measurements behind it03
Cost per solved taskNot computable$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 3 4B better than MiniMax M2.7 for coding?

Only MiniMax M2.7 has a coding score, 36.2 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 16.0x cheaper ($0.075 vs $1.20 per million).

Which is cheaper, Gemma 3 4B or MiniMax M2.7?

Gemma 3 4B costs $0.045 per million input tokens and $0.075 per million output tokens; MiniMax M2.7 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, Gemma 3 4B or MiniMax M2.7?

MiniMax M2.7, with 205K tokens against 131K.

How many benchmarks is the Gemma 3 4B vs MiniMax M2.7 comparison based on?

31 benchmarks have a result for both models as of October 22, 2026. Gemma 3 4B's coding index rests on 0 independent benchmarks and MiniMax M2.7's on 3. Where only one model has a result, the page says so instead of naming a winner.

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