Gemma 3 4B vs MiniMax M2.1

MiniMax M2.1 leads Gemma 3 4B on the Artificial Analysis Intelligence Index, 20.9 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; 11 benchmarks have a result for both.

Replace Gemma 3 4B Replace MiniMax M2.1

Gemma 3 4BGoogle

Coding: No data
Overall: 22.6
Output $/M: $0.075

MiniMax M2.1MiniMax

Coding: No data
Overall: No data
Output $/M: $1.20

vs boards won of 11 shared

Gemma 3 4B or MiniMax M2.1: which to pick

Neither model has a coding score yet, 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) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Model AGemma 3 4BGoogleNot benchmarkedNo coding benchmarkNo cost per solved task Model BMiniMax M2.1MiniMaxNot benchmarked1 independent benchmark$0.59 per solved task

113123

Shared results: 11
Gemma 3 4B only: 31
MiniMax M2.1 only: 23
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.

Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
MiniMax M2.1
MiniMax M2.1 leads, 20.9 against 4.8.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only MiniMax M2.1 has a GPQA Diamond result, 78.5%.
Directional only
Math
AIME
No call
Only MiniMax M2.1 has a AIME result, 77.9%.
Directional only
Knowledge
MMLU Pro
No call
Only MiniMax M2.1 has a MMLU Pro result, 87.0%.
Directional only
Web design
Design Arena: websites
No call
Only MiniMax M2.1 has a Design Arena: websites result, 1201.
Directional only
Long documents
Listed context window
MiniMax M2.1
MiniMax M2.1 takes 205K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 3 4B
Gemma 3 4B $0.0001, MiniMax M2.1 $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M2.1 has the number, $0.59.
Directional only

At a glance

Coding index: Gemma 3 4B not benchmarked, MiniMax M2.1 not benchmarked.
Widest category: Agentic work, 80.4 points apart on average over 1 shared benchmark.
Widest single gap: τ²-Bench Telecom: Gemma 3 4B 5.0% against MiniMax M2.1 85.4%, 80.4 points apart on a 0 to 100 scale.
Output price: Gemma 3 4B $0.075 against MiniMax M2.1 $1.20 per million output tokens, 16.0x apart.
Context window: Gemma 3 4B takes 131K tokens, MiniMax M2.1 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
Category	Gemma 3 4B	Bars	MiniMax M2.1	Ties
Coding	0		2
Intelligence	0		1
Agentic work	0		1
Reasoning	0		2
Math	0		2
Knowledge	0		1
General	0		2
All shared boards	0		11

CodingLike-for-likeSix of these boards feed the Vibe Coding Index02

Coding benchmarks for Gemma 3 4B and MiniMax M2.1
Benchmark	Gemma 3 4B	MiniMax M2.1	Leader
AA Coding Index	2.7	Not measured	Only Gemma 3 4B measured
LiveCodeBench (Vals AI)	Not measured	81.8%	Only MiniMax M2.1 measured
SWE-bench Verified (Vals AI)	Not measured	74.8%	Only MiniMax M2.1 measured
LiveCodeBench (Artificial Analysis run)	11.2%	81.0%	MiniMax M2.1
Terminal-Bench Hard (Artificial Analysis run)	0.8%	28.8%	MiniMax M2.1
Terminal-Bench	Not measured	36.6%	Only MiniMax M2.1 measured
ALE-Bench	Not measured	623.8	Only MiniMax M2.1 measured
LMArena Text: coding	1230	Not measured	Only Gemma 3 4B measured
LMArena Text: software and IT	1269	Not measured	Only Gemma 3 4B measured
SciCode	0.0%	Not measured	Only Gemma 3 4B measured
Neither model has a result on the other 29 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01

Intelligence benchmarks for Gemma 3 4B and MiniMax M2.1
Benchmark	Gemma 3 4B	MiniMax M2.1	Leader
AA Intelligence Index	4.8	20.9	MiniMax M2.1
Epoch Capabilities Index	115.9	Not measured	Only Gemma 3 4B measured

Agentic workLike-for-likePublic boards, shown as published, kept out of the index01

Agentic work benchmarks for Gemma 3 4B and MiniMax M2.1
Benchmark	Gemma 3 4B	MiniMax M2.1	Leader
τ²-Bench Telecom	5.0%	85.4%	MiniMax M2.1
Berkeley Function Calling Leaderboard (BFCL)	19.6%	Not measured	Only Gemma 3 4B measured
Neither model has a result on the other 39 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index02

Reasoning benchmarks for Gemma 3 4B and MiniMax M2.1
Benchmark	Gemma 3 4B	MiniMax M2.1	Leader
GPQA Diamond	Not measured	78.5%	Only MiniMax M2.1 measured
GPQA Diamond (Artificial Analysis run)	29.1%	83.0%	MiniMax M2.1
Humanity's Last Exam (Artificial Analysis run)	5.3%	23.2%	MiniMax M2.1
GPQA Diamond (Epoch AI run)	23.2%	Not measured	Only Gemma 3 4B measured
LMArena Text: hard prompts	1253	Not measured	Only Gemma 3 4B measured
LMArena Text: expert	1223	Not measured	Only Gemma 3 4B measured
LMArena Text: hard prompts in English	1253	Not measured	Only Gemma 3 4B measured
Kagi LLM Benchmark	25.2%	Not measured	Only 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 M2.1
Benchmark	Gemma 3 4B	MiniMax M2.1	Leader
AIME	Not measured	77.9%	Only MiniMax M2.1 measured
MATH 500 (Vals AI)	Not measured	89.0%	Only MiniMax M2.1 measured
MGSM (Vals AI)	Not measured	87.8%	Only MiniMax M2.1 measured
AA Math Index	12.7	82.7	MiniMax M2.1
AIME 2025 (Artificial Analysis run)	12.7%	82.7%	MiniMax M2.1
OTIS Mock AIME	7.5%	Not measured	Only Gemma 3 4B measured
LMArena Text: math	1239	Not measured	Only Gemma 3 4B measured
LMArena Text: mathematical work	1256	Not measured	Only 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 MiniMax M2.1
Benchmark	Gemma 3 4B	MiniMax M2.1	Leader
MMLU Pro	Not measured	87.0%	Only MiniMax M2.1 measured
LegalBench (Vals AI)	Not measured	75.5%	Only MiniMax M2.1 measured
CaseLaw (Vals AI)	Not measured	55.8%	Only MiniMax M2.1 measured
CorpFin (Vals AI)	Not measured	58.9%	Only MiniMax M2.1 measured
TaxEval (Vals AI)	Not measured	66.3%	Only MiniMax M2.1 measured
MedQA (Vals AI)	Not measured	91.2%	Only MiniMax M2.1 measured
MedCode (Vals AI)	Not measured	34.1%	Only MiniMax M2.1 measured
MMLU Pro (Artificial Analysis run)	41.7%	87.5%	MiniMax M2.1
LMArena Text: science	1306	Not measured	Only Gemma 3 4B measured
LMArena Text: medicine and healthcare	1342	Not measured	Only Gemma 3 4B measured
LMArena Text: legal and government	1327	Not measured	Only Gemma 3 4B measured
LMArena Text: business and finance	1311	Not measured	Only Gemma 3 4B measured
Neither model has a result on the other 6 boards here

Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared

Web design benchmarks for Gemma 3 4B and MiniMax M2.1
Benchmark	Gemma 3 4B	MiniMax M2.1	Leader
Design Arena: websites	Not measured	1201	Only MiniMax M2.1 measured
Design Arena: UI components	Not measured	1220	Only MiniMax M2.1 measured
Design Arena: game dev	Not measured	1134	Only MiniMax M2.1 measured
Design Arena: data viz	Not measured	1206	Only MiniMax M2.1 measured
Design Arena: 3D	Not measured	1164	Only MiniMax M2.1 measured
Design Arena: all code categories	Not measured	1190	Only MiniMax M2.1 measured
Design Arena: SVG	Not measured	1131	Only MiniMax M2.1 measured
Neither model has a result on the other 2 boards here

GeneralLike-for-likePublic boards, shown as published, kept out of the index02

General benchmarks for Gemma 3 4B and MiniMax M2.1
Benchmark	Gemma 3 4B	MiniMax M2.1	Leader
MedScribe (Vals AI)	Not measured	80.8%	Only MiniMax M2.1 measured
IFBench	28.3%	69.9%	MiniMax M2.1
Long context reasoning (AA-LCR)	6.7%	67.7%	MiniMax M2.1
DTBench	50.9%	Not measured	Only Gemma 3 4B measured
LMCA	2.8%	Not measured	Only Gemma 3 4B measured
LMArena Text	1291	Not measured	Only Gemma 3 4B measured
LMArena Text: instruction following	1239	Not measured	Only Gemma 3 4B measured
LMArena Text: creative writing	1270	Not measured	Only Gemma 3 4B measured
LMArena Text: English	1300	Not measured	Only Gemma 3 4B measured
LMArena Text: non-English	1273	Not measured	Only Gemma 3 4B measured
LMArena Text: German	1281	Not measured	Only Gemma 3 4B measured
LMArena Text: Russian	1294	Not measured	Only Gemma 3 4B measured
LMArena Text: multi-turn	1255	Not measured	Only Gemma 3 4B measured
LMArena Text: longer queries	1273	Not measured	Only Gemma 3 4B measured
LMArena Text: writing and language	1288	Not measured	Only Gemma 3 4B measured
LMArena Text: entertainment and media	1233	Not measured	Only 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 MiniMax M2.1
Benchmark	Gemma 3 4B	MiniMax M2.1	Leader
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 M2.1$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 M2.1$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 M2.1$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 M2.1
Specification	Google Gemma 3 4B	MiniMax M2.1
Maker	Google	MiniMax
Weights	Open weights	Open weights
Released	March 13, 2025	December 23, 2025
Context window	131K	205K
Input $/Mtok	$0.045	$0.30
Output $/Mtok	$0.075	$1.20
Coding index	Not benchmarked	Not benchmarked
Independent measurements behind it	0	1
Cost per solved task	Not computable	$0.59
Source	OpenRouter listing	OpenRouter listing

Questions

Is Gemma 3 4B better than MiniMax M2.1 for coding?

Neither model has a coding score yet, 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) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Which is cheaper, Gemma 3 4B or MiniMax M2.1?

Gemma 3 4B costs $0.045 per million input tokens and $0.075 per million output tokens; MiniMax M2.1 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.1 only.

Which has the bigger context window, Gemma 3 4B or MiniMax M2.1?

MiniMax M2.1, with 205K tokens against 131K.

How many benchmarks is the Gemma 3 4B vs MiniMax M2.1 comparison based on?

11 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 M2.1's on 1. Where only one model has a result, the page says so instead of naming a winner.

Gemma 3 4B or MiniMax M2.1: which to pick

Which one for your work

Coding

Intelligence

Reasoning

Math

Knowledge

Web design

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next