Model comparison
Gemma 4 12B vs MiniMax M2.7
Head-to-head evidence from 12 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
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 | Gemma 4 12B | Δ | MiniMax M2.7 |
|---|---|---|---|
| Agentic | Gemma 4 12BNot measured | MarginNo overlap | MiniMax M2.757.0 |
| Coding | Gemma 4 12BNot measured | MarginNo overlap | MiniMax M2.753.3 |
| Reasoning | Gemma 4 12B43.4 | MarginNo overlap | MiniMax M2.7Not measured |
| Knowledge | Gemma 4 12B77.5 | MarginNo overlap | MiniMax M2.7Not measured |
| Math | Gemma 4 12B77.5 | MarginNo overlap | MiniMax M2.7Not measured |
| Multimodal | Gemma 4 12B69.1 | MarginNo overlap | MiniMax M2.7Not measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemma 4 12B | MiniMax M2.7 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemma 4 12BNot available | MiniMax M2.7$0.3 input / $1.2 output | A complete price comparison is not available. |
| Generation speedtokens per second | Gemma 4 12BNot available | MiniMax M2.745 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemma 4 12BNot available | MiniMax M2.72.53 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemma 4 12B256K | MiniMax M2.7200K | Gemma 4 12B lists the larger context window. |
Benchmark Deep Dive
Agentic11 benchmarks
| Benchmark | Gemma 4 12B | MiniMax M2.7 | Result |
|---|---|---|---|
| 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 | — | 1158 | Not comparable |
| Gert LabsSource | — | 40.40% | Not comparable |
Coding11 benchmarks
| Benchmark | Gemma 4 12B | MiniMax M2.7 | Result |
|---|---|---|---|
| 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 |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | Gemma 4 12B | MiniMax M2.7 | Result |
|---|---|---|---|
| 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 |
Math2 benchmarks
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | Gemma 4 12B | MiniMax M2.7 | Result |
|---|---|---|---|
| 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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