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Model comparison

Gemma 4 12B vs MiniMax M2.7

Data verified

Head-to-head evidence from 12 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

47.29/100
Margin
16.8pts
winning →
64.11/100
0 category wins0 category wins

Public leaderboard positions: Gemma 4 12B #137 (Estimated); MiniMax M2.7 #36 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Gemma 4 12B and MiniMax M2.7 share 12 comparable benchmark results. 0 of 8 categories are comparable. 11 results are unique to Gemma 4 12B; 23 to MiniMax M2.7.

Updated July 23, 2026
Shared results
12
Gemma 4 12B only
11
MiniMax M2.7 only
23
Comparable categories
0 / 8

Benchmark data for Gemma 4 12B and MiniMax M2.7 is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 5 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

Gemma 4 12B has the larger context window at 256K, compared with 200K for MiniMax M2.7.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for Gemma 4 12B and MiniMax M2.7
CategoryGemma 4 12BΔMiniMax M2.7
AgenticGemma 4 12BNot measuredMarginNo overlapMiniMax M2.757.0
CodingGemma 4 12BNot measuredMarginNo overlapMiniMax M2.753.3
ReasoningGemma 4 12B43.4MarginNo overlapMiniMax M2.7Not measured
KnowledgeGemma 4 12B77.5MarginNo overlapMiniMax M2.7Not measured
MathGemma 4 12B77.5MarginNo overlapMiniMax M2.7Not measured
MultimodalGemma 4 12B69.1MarginNo overlapMiniMax M2.7Not measured

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricGemma 4 12BMiniMax M2.7Comparison
Input / output priceUSD per 1M tokensGemma 4 12BNot availableMiniMax M2.7$0.3 input / $1.2 outputA complete price comparison is not available.
Generation speedtokens per secondGemma 4 12BNot availableMiniMax M2.745 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenGemma 4 12BNot availableMiniMax M2.72.53 sA complete latency comparison is not available.
Context windowmaximum listed tokensGemma 4 12B256KMiniMax M2.7200KGemma 4 12B lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGemma 4 12BMiniMax M2.7Result
τ²-bench resultsSource 36.3%84.8%MiniMax M2.7 leads
Terminal-Bench 2.0Source 57%Not comparable
ToolathlonSource 46.3%Not comparable
MLE-Bench LiteSource 66.6%Not comparable
MM-ClawBenchSource 62.7%Not comparable
Claw-EvalSource 48.7%Not comparable
AA Agentic IndexSource 25.6%Not comparable
APEX-Agents-AASource 10.6%Not comparable
GDPval-AASource 32.9%Not comparable
GDPval-AASource 1158Not comparable
Gert LabsSource 40.40%Not comparable
Coding
BenchmarkGemma 4 12BMiniMax M2.7Result
AA-SciCodeSource 38.2%47.0%MiniMax M2.7 leads
SWE-bench Verified*Source 75.4%Not comparable
SWE-bench ProSource 56.2%Not comparable
SWE-RebenchSource 51.9%Not comparable
SWE MultilingualSource 76.5%Not comparable
Multi-SWE BenchSource 52.7%Not comparable
VIBE-ProSource 55.6%Not comparable
NL2RepoSource 39.8%Not comparable
Vibe Code BenchSource 27.04%Not comparable
React Native EvalsSource 71.4%Not comparable
AA Coding IndexSource 52.6%Not comparable
Reasoning
BenchmarkGemma 4 12BMiniMax M2.7Result
BBHSource 53%Not comparable
MRCRv2Source 43.4%Not comparable
AA-LCRSource 55.3%68.7%MiniMax M2.7 leads
CritPtSource 0.0%0.6%MiniMax M2.7 leads
Knowledge
BenchmarkGemma 4 12BMiniMax M2.7Result
GPQASource 78.8%Not comparable
GPQA-DSource 78.8%87.0%MiniMax M2.7 leads
MMLU-ProSource 77.2%Not comparable
HLE w/o toolsSource 5.2%Not comparable
MMMLUSource 83.4%Not comparable
Artificial Analysis Intelligence IndexSource 22.0%38.1%MiniMax M2.7 leads
AA-GPQA DiamondSource 75.3%87.4%MiniMax M2.7 leads
AA-HLESource 14.8%28.1%MiniMax M2.7 leads
AA-Omniscience IndexSource -51.9%0.7%MiniMax M2.7 leads
AA-Omniscience AccuracySource 16.0%26.1%MiniMax M2.7 leads
AA-Omniscience Hallucination RateSource 80.8%34.4%MiniMax M2.7 leads
MMLU-Pro (Arcee)Source 80.8%Not comparable
Math
BenchmarkGemma 4 12BMiniMax M2.7Result
AIME26Source 77.5%Not comparable
AIME25 (Arcee)Source 80.0%Not comparable
Multimodal
BenchmarkGemma 4 12BMiniMax M2.7Result
MMMU-ProSource 69.1%Not comparable
MathVisionSource 79.7%Not comparable
MedXpertQA (MM)Source 48.7%Not comparable
AA-MMMU-ProSource 69.7%Not comparable
Design Arena WebsiteSource 1275Not comparable
Inst. Following
BenchmarkGemma 4 12BMiniMax M2.7Result
AA-IFBenchSource 73.5%75.7%MiniMax M2.7 leads
Frequently Asked Questions (3)

Can I compare Gemma 4 12B and MiniMax M2.7 on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for Gemma 4 12B and MiniMax M2.7 today?

MiniMax M2.7: $0.30 input / $1.20 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

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Last updated: July 23, 2026

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