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Gemma 4 26B A4B vs MiniMax M2.7

MiniMax M2.7 leads Gemma 4 26B A4B on the Artificial Analysis Intelligence Index, 22.8 to 16.7, and Gemma 4 26B A4B costs 2.0x less per output token ($0.60 vs $1.20 per million). Updated October 22, 2026; 40 benchmarks have a result for both.

Replace Gemma 4 26B A4B Replace MiniMax M2.7
Gemma 4 26B A4BGoogle
Coding
No data
Overall
54.7
Output $/M
$0.60
24
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
16
vs boards won of 40 shared

Gemma 4 26B A4B or MiniMax M2.7: which to pick

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Gemma 4 26B A4B has none, so the two cannot be ranked on coding.

Pick Gemma 4 26B A4B for output tokens 2.0x cheaper ($0.60 vs $1.20 per million) and a larger context window (262K against 205K tokens).

Model AGemma 4 26B A4BGoogleNot benchmarked1 independent benchmarkNo cost per solved taskModel BMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved task
Shared results
40
Gemma 4 26B A4B only
15
MiniMax M2.7 only
34
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 4 26B A4B not benchmarked, MiniMax M2.7 36.2 from 3 benchmarks.
Widest category
Agentic work, 26.8 points apart on average over 2 shared benchmarks.
Widest single gap
τ²-Bench Telecom: Gemma 4 26B A4B 43.6% against MiniMax M2.7 84.8%, 41.2 points apart on a 0 to 100 scale.
Output price
Gemma 4 26B A4B $0.60 against MiniMax M2.7 $1.20 per million output tokens, 2.0x apart.
Context window
Gemma 4 26B A4B takes 262K 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 4 26B A4BBarsMiniMax M2.7Ties
Coding28
Intelligence02
Agentic work02
Reasoning32
Math20
Knowledge40
General132
All shared boards2416
CodingLike-for-likeSix of these boards feed the Vibe Coding Index28
Coding benchmarks for Gemma 4 26B A4B and MiniMax M2.7
BenchmarkGemma 4 26B A4BMiniMax M2.7Leader
LMArena WebDev13601399MiniMax M2.7
AA Coding Index39.352.6MiniMax 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
SciCode40.0%50.1%MiniMax M2.7
Terminal-Bench Hard (Artificial Analysis run)25.0%39.4%MiniMax M2.7
Terminal-BenchNot measured45.1%Only MiniMax M2.7 measured
WeirdML35.2%37.0%MiniMax M2.7
ALE-Bench927.2599.3Gemma 4 26B A4B
LMArena Text: coding14461454MiniMax M2.7
LMArena Text: software and IT14541446Gemma 4 26B A4B
LMArena WebDev: React13511388MiniMax M2.7
LMArena WebDev: HTML13621401MiniMax M2.7
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemma 4 26B A4B and MiniMax M2.7
BenchmarkGemma 4 26B A4BMiniMax M2.7Leader
AA Intelligence Index16.722.8MiniMax M2.7
Epoch Capabilities Index141.9145.8MiniMax M2.7
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Gemma 4 26B A4B and MiniMax M2.7
BenchmarkGemma 4 26B A4BMiniMax M2.7Leader
AA Agentic Index2.915.3MiniMax M2.7
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 Telecom43.6%84.8%MiniMax M2.7
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index32
Reasoning benchmarks for Gemma 4 26B A4B and MiniMax M2.7
BenchmarkGemma 4 26B A4BMiniMax M2.7Leader
GPQA DiamondNot measured86.6%Only MiniMax M2.7 measured
GPQA Diamond (Artificial Analysis run)79.2%87.4%MiniMax M2.7
Humanity's Last Exam (Artificial Analysis run)19.3%29.6%MiniMax M2.7
GPQA Diamond (Epoch AI run)73.2%Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: hard prompts14381422Gemma 4 26B A4B
LMArena Text: expert14471443Gemma 4 26B A4B
LMArena Text: hard prompts in English14481441Gemma 4 26B A4B
LMArena Vision: diagrams1264Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: homework1293Not measuredOnly Gemma 4 26B A4B measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Gemma 4 26B A4B and MiniMax M2.7
BenchmarkGemma 4 26B A4BMiniMax M2.7Leader
AIMENot measured91.0%Only MiniMax M2.7 measured
OTIS Mock AIME82.2%Not measuredOnly Gemma 4 26B A4B measured
ProofBenchNot measured3.0%Only MiniMax M2.7 measured
LMArena Text: math14701421Gemma 4 26B A4B
LMArena Text: mathematical work14751437Gemma 4 26B A4B
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Gemma 4 26B A4B and MiniMax M2.7
BenchmarkGemma 4 26B A4BMiniMax 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
LMArena Text: science14461416Gemma 4 26B A4B
LMArena Text: medicine and healthcare14281409Gemma 4 26B A4B
LMArena Text: legal and government14571403Gemma 4 26B A4B
LMArena Text: business and finance14291407Gemma 4 26B A4B
FACTS Benchmark Suite42.7%Not measuredOnly Gemma 4 26B A4B measured
Neither model has a result on the other 9 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Gemma 4 26B A4B and MiniMax M2.7
BenchmarkGemma 4 26B A4BMiniMax M2.7Leader
Design Arena: websitesNot measured1242Only MiniMax M2.7 measured
Design Arena: UI componentsNot measured1207Only 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 measured1194Only 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 index132
General benchmarks for Gemma 4 26B A4B and MiniMax M2.7
BenchmarkGemma 4 26B A4BMiniMax M2.7Leader
MedScribe (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
IFBench72.4%75.7%MiniMax M2.7
Long context reasoning (AA-LCR)65.7%78.3%MiniMax M2.7
DTBench74.9%Not measuredOnly Gemma 4 26B A4B measured
LMCA29.7%Not measuredOnly Gemma 4 26B A4B measured
ExploitBenchNot measured13.3%Only MiniMax M2.7 measured
LMArena Text14341405Gemma 4 26B A4B
LMArena Text: instruction following14201405Gemma 4 26B A4B
LMArena Text: creative writing14001354Gemma 4 26B A4B
LMArena Vision1260Not measuredOnly Gemma 4 26B A4B measured
LMArena Text: English14441426Gemma 4 26B A4B
LMArena Text: non-English14211382Gemma 4 26B A4B
LMArena Text: Chinese14951442Gemma 4 26B A4B
LMArena Text: GermanNot measured1398Only MiniMax M2.7 measured
LMArena Text: JapaneseNot measured1260Only MiniMax M2.7 measured
LMArena Text: KoreanNot measured1314Only MiniMax M2.7 measured
LMArena Text: French14601424Gemma 4 26B A4B
LMArena Text: Spanish14151402Gemma 4 26B A4B
LMArena Text: Russian14341383Gemma 4 26B A4B
LMArena Text: PolishNot measured1387Only MiniMax M2.7 measured
LMArena Text: multi-turn14411412Gemma 4 26B A4B
LMArena Text: longer queries14271418Gemma 4 26B A4B
LMArena Text: writing and language14051376Gemma 4 26B A4B
LMArena Text: entertainment and media14031360Gemma 4 26B A4B
LMArena Vision: English1256Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: Chinese1312Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: reading text1268Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: humor1272Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: captioning1297Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: recognizing things1191Not measuredOnly Gemma 4 26B A4B measured
LMArena Vision: creative writing1256Not measuredOnly Gemma 4 26B A4B measured
Neither model has a result on the other 17 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemma 4 26B A4B and MiniMax M2.7
BenchmarkGemma 4 26B A4BMiniMax 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 4 26B A4B$0.0004Fits in one request
MiniMax M2.7$0.0009Fits in one request

Gemma 4 26B A4B costs less

Repository review

50K input + 3K output tokens

Gemma 4 26B A4B$0.0093Fits in one request
MiniMax M2.7$0.019Fits in one request

Gemma 4 26B A4B costs less

Agent loop

200K input + 10K output tokens

Gemma 4 26B A4B$0.036Fits in one request
MiniMax M2.7$0.072Exceeds the context window

Gemma 4 26B A4B 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 4 26B A4B and MiniMax M2.7
SpecificationGoogle Gemma 4 26B A4BMiniMax M2.7
MakerGoogleMiniMax
WeightsOpen weightsOpen weights
ReleasedApril 3, 2026March 18, 2026
Context window262K205K
Input $/Mtok$0.15$0.30
Output $/Mtok$0.60$1.20
Coding indexNot benchmarked36.2
Independent measurements behind it13
Cost per solved taskNot computable$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 4 26B A4B better than MiniMax M2.7 for coding?

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Gemma 4 26B A4B has none, so the two cannot be ranked on coding. Pick Gemma 4 26B A4B for output tokens 2.0x cheaper ($0.60 vs $1.20 per million) and a larger context window (262K against 205K tokens).

Which is cheaper, Gemma 4 26B A4B or MiniMax M2.7?

Gemma 4 26B A4B costs $0.15 per million input tokens and $0.60 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 4 26B A4B or MiniMax M2.7?

Gemma 4 26B A4B, with 262K tokens against 205K.

How many benchmarks is the Gemma 4 26B A4B vs MiniMax M2.7 comparison based on?

40 benchmarks have a result for both models as of October 22, 2026. Gemma 4 26B A4B's coding index rests on 1 independent benchmark 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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