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Gemma 2 27B vs MiniMax M2.5

Gemma 2 27B costs 1.8x less per output token than MiniMax M2.5 ($0.65 vs $1.20 per million). Updated October 22, 2026; 30 benchmarks have a result for both.

Gemma 2 27BGoogle
Coding
No data
Overall
No data
Output $/M
$0.65
1
MiniMax M2.5MiniMax
Coding
37.2
Overall
37.3
Output $/M
$1.20
29
vs boards won of 30 shared

Gemma 2 27B or MiniMax M2.5: which to pick

Only MiniMax M2.5 has a coding score, 37.2 on the Vibe Coding Index; Gemma 2 27B has none, so the two cannot be ranked on coding.

Pick Gemma 2 27B for output tokens 1.8x cheaper ($0.65 vs $1.20 per million) and work measured by LMArena Text: Japanese, where it leads.

Shared results
30
Gemma 2 27B only
6
MiniMax M2.5 only
38
Like-for-like categories
6 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 2 27B not benchmarked, MiniMax M2.5 37.2 from 3 benchmarks.
Widest category
Reasoning, 31.0 points apart on average over 3 shared benchmarks.
Widest single gap
LMArena Text: expert: Gemma 2 27B 1171 against MiniMax M2.5 1378, 34.5 points apart on a 0 to 100 scale.
Output price
Gemma 2 27B $0.65 against MiniMax M2.5 $1.20 per million output tokens, 1.8x apart.
Context window
Gemma 2 27B takes 8K tokens, MiniMax M2.5 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 2 27BBarsMiniMax M2.5Ties
Coding02
Intelligence01
Reasoning03
Math02
Knowledge05
General116
All shared boards129
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Gemma 2 27B and MiniMax M2.5
BenchmarkGemma 2 27BMiniMax M2.5Leader
SWE-bench VerifiedNot measured75.8%Only MiniMax M2.5 measured
SWE-bench MultilingualNot measured68.3%Only MiniMax M2.5 measured
LMArena WebDevNot measured1386Only MiniMax M2.5 measured
LiveCodeBench (Vals AI)Not measured79.2%Only MiniMax M2.5 measured
SWE-bench Verified (Vals AI)Not measured74.2%Only MiniMax M2.5 measured
Vibe Code Bench (Vals AI)Not measured14.8%Only MiniMax M2.5 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured34.8%Only MiniMax M2.5 measured
Terminal-BenchNot measured42.7%Only MiniMax M2.5 measured
ALE-BenchNot measured618.2Only MiniMax M2.5 measured
LMArena Text: coding12111380MiniMax M2.5
LMArena Text: software and IT12281383MiniMax M2.5
LMArena WebDev: ReactNot measured1374Only MiniMax M2.5 measured
LMArena WebDev: HTMLNot measured1414Only MiniMax M2.5 measured
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Gemma 2 27B and MiniMax M2.5
BenchmarkGemma 2 27BMiniMax M2.5Leader
AA Intelligence IndexNot measured22.8Only MiniMax M2.5 measured
Epoch Capabilities Index122.1146.6MiniMax M2.5
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for Gemma 2 27B and MiniMax M2.5
BenchmarkGemma 2 27BMiniMax M2.5Leader
τ²-Bench TelecomNot measured95.3%Only MiniMax M2.5 measured
Vending-Bench 2Not measured-$23Only MiniMax M2.5 measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for Gemma 2 27B and MiniMax M2.5
BenchmarkGemma 2 27BMiniMax M2.5Leader
GPQA DiamondNot measured82.1%Only MiniMax M2.5 measured
GPQA Diamond (Artificial Analysis run)Not measured84.8%Only MiniMax M2.5 measured
Humanity's Last Exam (Artificial Analysis run)Not measured20.5%Only MiniMax M2.5 measured
GPQA Diamond (Epoch AI run)36.5%Not measuredOnly Gemma 2 27B measured
ARC-AGINot measured63.7%Only MiniMax M2.5 measured
ARC-AGI-2Not measured4.9%Only MiniMax M2.5 measured
LMArena Text: hard prompts11981372MiniMax M2.5
LMArena Text: expert11711378MiniMax M2.5
LMArena Text: hard prompts in English12061384MiniMax M2.5
Kagi LLM BenchmarkNot measured55.2%Only MiniMax M2.5 measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Gemma 2 27B and MiniMax M2.5
BenchmarkGemma 2 27BMiniMax M2.5Leader
AIMENot measured88.8%Only MiniMax M2.5 measured
OTIS Mock AIME1.4%Not measuredOnly Gemma 2 27B measured
ProofBenchNot measured4.0%Only MiniMax M2.5 measured
MATH level 527.9%Not measuredOnly Gemma 2 27B measured
LMArena Text: math12121378MiniMax M2.5
LMArena Text: mathematical work12211378MiniMax M2.5
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for Gemma 2 27B and MiniMax M2.5
BenchmarkGemma 2 27BMiniMax M2.5Leader
MMLU ProNot measured80.1%Only MiniMax M2.5 measured
LegalBench (Vals AI)68.0%80.0%MiniMax M2.5
CaseLaw (Vals AI)Not measured53.5%Only MiniMax M2.5 measured
CorpFin (Vals AI)Not measured59.6%Only MiniMax M2.5 measured
TaxEval (Vals AI)Not measured68.2%Only MiniMax M2.5 measured
MedQA (Vals AI)Not measured92.5%Only MiniMax M2.5 measured
MMLU75.7%Not measuredOnly Gemma 2 27B measured
LMArena Text: science12281369MiniMax M2.5
LMArena Text: medicine and healthcare11981357MiniMax M2.5
LMArena Text: legal and government12411366MiniMax M2.5
LMArena Text: business and finance12081356MiniMax M2.5
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for Gemma 2 27B and MiniMax M2.5
BenchmarkGemma 2 27BMiniMax M2.5Leader
Design Arena: websitesNot measured1222Only MiniMax M2.5 measured
Design Arena: UI componentsNot measured1170Only MiniMax M2.5 measured
Design Arena: game devNot measured1176Only MiniMax M2.5 measured
Design Arena: data vizNot measured1172Only MiniMax M2.5 measured
Design Arena: 3DNot measured1170Only MiniMax M2.5 measured
Design Arena: all code categoriesNot measured1207Only MiniMax M2.5 measured
Design Arena: SVGNot measured1150Only MiniMax M2.5 measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index116
General benchmarks for Gemma 2 27B and MiniMax M2.5
BenchmarkGemma 2 27BMiniMax M2.5Leader
IFBenchNot measured71.6%Only MiniMax M2.5 measured
Long context reasoning (AA-LCR)Not measured73.3%Only MiniMax M2.5 measured
DTBench48.0%Not measuredOnly Gemma 2 27B measured
LMCA7.1%Not measuredOnly Gemma 2 27B measured
CL-benchNot measured11.4%Only MiniMax M2.5 measured
CL-bench LifeNot measured6.3%Only MiniMax M2.5 measured
LMArena Text12311359MiniMax M2.5
LMArena Text: instruction following12061353MiniMax M2.5
LMArena Text: creative writing12401331MiniMax M2.5
LMArena Text: English12421380MiniMax M2.5
LMArena Text: non-English12171338MiniMax M2.5
LMArena Text: Chinese12211393MiniMax M2.5
LMArena Text: German12091361MiniMax M2.5
LMArena Text: Japanese11751171Gemma 2 27B
LMArena Text: Korean11741233MiniMax M2.5
LMArena Text: French12481363MiniMax M2.5
LMArena Text: Spanish12281353MiniMax M2.5
LMArena Text: Russian12341359MiniMax M2.5
LMArena Text: Polish12771334MiniMax M2.5
LMArena Text: multi-turn12241364MiniMax M2.5
LMArena Text: longer queries12301366MiniMax M2.5
LMArena Text: writing and language12491345MiniMax M2.5
LMArena Text: entertainment and media12121329MiniMax M2.5
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 2 27B and MiniMax M2.5
BenchmarkGemma 2 27BMiniMax M2.5Leader
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 2 27B$0.0010Fits in one request
MiniMax M2.5$0.0009Fits in one request

MiniMax M2.5 costs less

Repository review

50K input + 3K output tokens

Gemma 2 27B$0.034Exceeds the context window
MiniMax M2.5$0.019Fits in one request

MiniMax M2.5 costs less

Agent loop

200K input + 10K output tokens

Gemma 2 27B$0.137Exceeds the context window
MiniMax M2.5$0.072Exceeds the context window

MiniMax M2.5 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 2 27B and MiniMax M2.5
SpecificationGoogle Gemma 2 27BMiniMax M2.5
MakerGoogleMiniMax
WeightsOpen weightsOpen weights
ReleasedJuly 13, 2024February 12, 2026
Context window8K205K
Input $/Mtok$0.65$0.30
Output $/Mtok$0.65$1.20
Coding indexNot benchmarked37.2
Independent measurements behind it03
Cost per solved taskNot computable$0.62
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 2 27B better than MiniMax M2.5 for coding?

Only MiniMax M2.5 has a coding score, 37.2 on the Vibe Coding Index; Gemma 2 27B has none, so the two cannot be ranked on coding. Pick Gemma 2 27B for output tokens 1.8x cheaper ($0.65 vs $1.20 per million) and work measured by LMArena Text: Japanese, where it leads.

Which is cheaper, Gemma 2 27B or MiniMax M2.5?

Gemma 2 27B costs $0.65 per million input tokens and $0.65 per million output tokens; MiniMax M2.5 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.5 only.

Which has the bigger context window, Gemma 2 27B or MiniMax M2.5?

MiniMax M2.5, with 205K tokens against 8K.

How many benchmarks is the Gemma 2 27B vs MiniMax M2.5 comparison based on?

30 benchmarks have a result for both models as of October 22, 2026. Gemma 2 27B's coding index rests on 0 independent benchmarks and MiniMax M2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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