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Gemma 4 31B vs MiniMax M2.7

Gemma 4 31B leads MiniMax M2.7 on coding, 39.0 to 36.2 on the Vibe Coding Index, and Gemma 4 31B costs 3.0x less per output token ($0.40 vs $1.20 per million). Updated October 22, 2026; 42 benchmarks have a result for both.

Replace Gemma 4 31B Replace MiniMax M2.7
Gemma 4 31BGoogle
Coding
39.0
Overall
42.1
Output $/M
$0.40
27
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
15
vs boards won of 42 shared

Gemma 4 31B or MiniMax M2.7: which to pick

Pick Gemma 4 31B for coding: it scores 39.0 on the Vibe Coding Index against 36.2 for MiniMax M2.7, though on 2 benchmarks against 3.

Pick MiniMax M2.7 for work measured by LMArena WebDev or AA Coding Index, where it leads.

Model AGemma 4 31BGoogle39.0/1002 independent benchmarksNo cost per solved taskModel BMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved task
Shared results
42
Gemma 4 31B only
29
MiniMax M2.7 only
32
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 31B 39.0 from 2 benchmarks, MiniMax M2.7 36.2 from 3 benchmarks.
Widest category
Agentic work, 15.2 points apart on average over 2 shared benchmarks.
Widest single gap
τ²-Bench Telecom: Gemma 4 31B 65.5% against MiniMax M2.7 84.8%, 19.3 points apart on a 0 to 100 scale.
Output price
Gemma 4 31B $0.40 against MiniMax M2.7 $1.20 per million output tokens, 3.0x apart.
Context window
Gemma 4 31B 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 31BBarsMiniMax M2.7Ties
Coding46
Intelligence02
Agentic work02
Reasoning32
Math20
Knowledge41
General142
All shared boards2715
CodingLike-for-likeSix of these boards feed the Vibe Coding Index46
Coding benchmarks for Gemma 4 31B and MiniMax M2.7
BenchmarkGemma 4 31BMiniMax M2.7Leader
LiveBench coding49.0%Not measuredOnly Gemma 4 31B measured
LMArena WebDev13671399MiniMax M2.7
AA Coding Index43.452.6MiniMax 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
SciCode45.5%50.1%MiniMax M2.7
Terminal-Bench Hard (Artificial Analysis run)36.4%39.4%MiniMax M2.7
Terminal-BenchNot measured45.1%Only MiniMax M2.7 measured
WeirdML52.3%37.0%Gemma 4 31B
ALE-Bench925.5599.3Gemma 4 31B
LMArena Text: coding14591454Gemma 4 31B
LMArena Text: software and IT14631446Gemma 4 31B
LMArena WebDev: React13591388MiniMax M2.7
LMArena WebDev: HTML13801401MiniMax M2.7
SciCode8.9%Not measuredOnly Gemma 4 31B 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 4 31B and MiniMax M2.7
BenchmarkGemma 4 31BMiniMax M2.7Leader
AA Intelligence Index14.722.8MiniMax M2.7
Epoch Capabilities Index143.0145.8MiniMax M2.7
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Gemma 4 31B and MiniMax M2.7
BenchmarkGemma 4 31BMiniMax M2.7Leader
AA Agentic Index4.215.3MiniMax M2.7
LiveBench research44.4%Not measuredOnly Gemma 4 31B measured
LiveBench browser4.0%Not measuredOnly Gemma 4 31B measured
LiveBench long agentic13.3%Not measuredOnly Gemma 4 31B 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 Telecom65.5%84.8%MiniMax M2.7
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index32
Reasoning benchmarks for Gemma 4 31B and MiniMax M2.7
BenchmarkGemma 4 31BMiniMax M2.7Leader
GPQA DiamondNot measured86.6%Only MiniMax M2.7 measured
LiveBench reasoning68.3%Not measuredOnly Gemma 4 31B measured
GPQA Diamond (Artificial Analysis run)85.7%87.4%MiniMax M2.7
Humanity's Last Exam (Artificial Analysis run)23.6%29.6%MiniMax M2.7
GPQA Diamond (Epoch AI run)75.8%Not measuredOnly Gemma 4 31B measured
LMArena Text: hard prompts14481422Gemma 4 31B
LMArena Text: expert14641443Gemma 4 31B
LMArena Text: hard prompts in English14561441Gemma 4 31B
LMArena Vision: diagrams1283Not measuredOnly Gemma 4 31B measured
LMArena Vision: homework1310Not measuredOnly Gemma 4 31B measured
Kagi LLM Benchmark63.5%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Gemma 4 31B and MiniMax M2.7
BenchmarkGemma 4 31BMiniMax M2.7Leader
AIMENot measured91.0%Only MiniMax M2.7 measured
OTIS Mock AIME73.3%Not measuredOnly Gemma 4 31B measured
ProofBenchNot measured3.0%Only MiniMax M2.7 measured
LMArena Text: math14631421Gemma 4 31B
LMArena Text: mathematical work14651437Gemma 4 31B
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
Knowledge benchmarks for Gemma 4 31B and MiniMax M2.7
BenchmarkGemma 4 31BMiniMax 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)52.6%60.9%MiniMax M2.7
CorpFin (Vals AI)Not measured61.2%Only MiniMax M2.7 measured
TaxEval (Vals AI)Not measured66.6%Only MiniMax M2.7 measured
MortgageTax (Vals AI)61.4%Not measuredOnly Gemma 4 31B measured
MedCode (Vals AI)Not measured34.4%Only MiniMax M2.7 measured
SimpleQA Verified10.4%Not measuredOnly Gemma 4 31B measured
LMArena Text: science14571416Gemma 4 31B
LMArena Text: medicine and healthcare14511409Gemma 4 31B
LMArena Text: legal and government14381403Gemma 4 31B
LMArena Text: business and finance14301407Gemma 4 31B
FACTS Benchmark Suite45.3%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 5 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for Gemma 4 31B and MiniMax M2.7
BenchmarkGemma 4 31BMiniMax 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
LiveBench design58.4%Not measuredOnly Gemma 4 31B measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index142
General benchmarks for Gemma 4 31B and MiniMax M2.7
BenchmarkGemma 4 31BMiniMax M2.7Leader
LiveBench data analysis53.3%Not measuredOnly Gemma 4 31B measured
SAGE (Vals AI)55.0%Not measuredOnly Gemma 4 31B measured
MedScribe (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
IFBench75.6%75.7%MiniMax M2.7
Long context reasoning (AA-LCR)69.7%78.3%MiniMax M2.7
DTBench82.7%Not measuredOnly Gemma 4 31B measured
LMCA39.3%Not measuredOnly Gemma 4 31B measured
Surface Evolver Bench30.6%Not measuredOnly Gemma 4 31B measured
ExploitBenchNot measured13.3%Only MiniMax M2.7 measured
LMArena Text14431405Gemma 4 31B
LMArena Text: instruction following14331405Gemma 4 31B
LMArena Text: creative writing14171354Gemma 4 31B
LMArena Vision1276Not measuredOnly Gemma 4 31B measured
LMArena Text: English14511426Gemma 4 31B
LMArena Text: non-English14301382Gemma 4 31B
LMArena Text: Chinese14751442Gemma 4 31B
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: French14361424Gemma 4 31B
LMArena Text: Spanish14421402Gemma 4 31B
LMArena Text: Russian14601383Gemma 4 31B
LMArena Text: Polish14331387Gemma 4 31B
LMArena Text: multi-turn14521412Gemma 4 31B
LMArena Text: longer queries14461418Gemma 4 31B
LMArena Text: writing and language14321376Gemma 4 31B
LMArena Text: entertainment and media14051360Gemma 4 31B
LMArena Vision: English1271Not measuredOnly Gemma 4 31B measured
LMArena Vision: Chinese1326Not measuredOnly Gemma 4 31B measured
LMArena Vision: reading text1282Not measuredOnly Gemma 4 31B measured
LMArena Vision: humor1280Not measuredOnly Gemma 4 31B measured
LMArena Vision: captioning1218Not measuredOnly Gemma 4 31B measured
LMArena Vision: recognizing things1226Not measuredOnly Gemma 4 31B measured
LMArena Vision: creative writing1285Not measuredOnly Gemma 4 31B measured
LMArena Document1425Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemma 4 31B and MiniMax M2.7
BenchmarkGemma 4 31BMiniMax 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 31B$0.0003Fits in one request
MiniMax M2.7$0.0009Fits in one request

Gemma 4 31B costs less

Repository review

50K input + 3K output tokens

Gemma 4 31B$0.0082Fits in one request
MiniMax M2.7$0.019Fits in one request

Gemma 4 31B costs less

Agent loop

200K input + 10K output tokens

Gemma 4 31B$0.032Fits in one request
MiniMax M2.7$0.072Exceeds the context window

Gemma 4 31B 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 31B and MiniMax M2.7
SpecificationGoogle Gemma 4 31BMiniMax M2.7
MakerGoogleMiniMax
WeightsOpen weightsOpen weights
ReleasedApril 2, 2026March 18, 2026
Context window262K205K
Input $/Mtok$0.14$0.30
Output $/Mtok$0.40$1.20
Coding index39.036.2
Independent measurements behind it23
Cost per solved taskNot computable$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 4 31B better than MiniMax M2.7 for coding?

Pick Gemma 4 31B for coding: it scores 39.0 on the Vibe Coding Index against 36.2 for MiniMax M2.7, though on 2 benchmarks against 3. Pick MiniMax M2.7 for work measured by LMArena WebDev or AA Coding Index, where it leads.

Which is cheaper, Gemma 4 31B or MiniMax M2.7?

Gemma 4 31B costs $0.14 per million input tokens and $0.40 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 31B or MiniMax M2.7?

Gemma 4 31B, with 262K tokens against 205K.

How many benchmarks is the Gemma 4 31B vs MiniMax M2.7 comparison based on?

42 benchmarks have a result for both models as of October 22, 2026. Gemma 4 31B's coding index rests on 2 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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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gemma-4-31b-it-vs-minimax-minimax-m2-7">LLMBenchmark.ai, Gemma 4 31B vs MiniMax M2.7</a></p>