Model comparison
Gemma 4 31B vs Mellum2-12B-A2.5B-Thinking
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemma 4 31B #43 (Supported); Mellum2-12B-A2.5B-Thinking unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemma 4 31B and Mellum2-12B-A2.5B-Thinking share 1 comparable benchmark result. 1 of 8 categories are comparable. 28 results are unique to Gemma 4 31B; 4 to Mellum2-12B-A2.5B-Thinking.
Updated July 23, 2026- Shared results
- 1
- Gemma 4 31B only
- 28
- Mellum2-12B-A2.5B-Thinking only
- 4
- Comparable categories
- 1 / 8
Treat this as a split decision. Gemma 4 31B makes more sense if you need the larger 256K context window; Mellum2-12B-A2.5B-Thinking is the better fit if knowledge is the priority.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Gemma 4 31B and Mellum2-12B-A2.5B-Thinking finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Gemma 4 31B gives you the larger context window at 256K, compared with 128K for Mellum2-12B-A2.5B-Thinking.
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 31B | Δ | Mellum2-12B-A2.5B-Thinking |
|---|---|---|---|
| Knowledge | Gemma 4 31B52.9 | Margin→ 4.7 | Mellum2-12B-A2.5B-Thinking57.6 |
| Coding | Gemma 4 31B41.6 | MarginNo overlap | Mellum2-12B-A2.5B-ThinkingNot measured |
| Multimodal | Gemma 4 31B76.9 | MarginNo overlap | Mellum2-12B-A2.5B-ThinkingNot measured |
| Inst. Following | Gemma 4 31BNot measured | MarginNo overlap | Mellum2-12B-A2.5B-Thinking76.5 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 84.3%B 57.6%Winner: Gemma 4 31BΔ 26.7GPQA: Gemma 4 31B scored 84.3%; Mellum2-12B-A2.5B-Thinking scored 57.6%. Gemma 4 31B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemma 4 31B | Mellum2-12B-A2.5B-Thinking | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemma 4 31B$0 input / $0 output | Mellum2-12B-A2.5B-ThinkingNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Gemma 4 31BNot available | Mellum2-12B-A2.5B-ThinkingNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemma 4 31BNot available | Mellum2-12B-A2.5B-ThinkingNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemma 4 31B256K | Mellum2-12B-A2.5B-Thinking128K | Gemma 4 31B lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | Gemma 4 31B | Mellum2-12B-A2.5B-Thinking | Result |
|---|---|---|---|
| AA Agentic IndexSource | 14.4% | — | Not comparable |
| τ²-bench resultsSource | 59.9% | — | Not comparable |
| GDPval-AASource | 15.2% | — | Not comparable |
| GDPval-AASource | 804 | — | Not comparable |
| Gert LabsSource | 35.26% | — | Not comparable |
| AA EnterpriseOps-GymSource | 28.3% | — | Not comparable |
| AA ITBenchSource | 37.3% | — | Not comparable |
| AA Tau3 BankingSource | 15.1% | — | Not comparable |
| terminalBenchHardSource | 36.4% | — | Not comparable |
| BFCL v4Source | — | 45.6% | Not comparable |
Coding4 benchmarks
Reasoning2 benchmarks
KnowledgeMellum2-12B-A2.5B-Thinking wins13 benchmarks
| Benchmark | Gemma 4 31B | Mellum2-12B-A2.5B-Thinking | Result |
|---|---|---|---|
| GPQASource | 84.3% | 57.6% | Gemma 4 31B leads |
| MMLU-ProSource | 85.2% | — | Not comparable |
| HLESource | 26.5% | — | Not comparable |
| HLE w/o toolsSource | 19.5% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 29.4% | — | Not comparable |
| AA-GPQA DiamondSource | 85.7% | — | Not comparable |
| AA-HLESource | 22.7% | — | Not comparable |
| AA-Omniscience IndexSource | -45.4% | — | Not comparable |
| AA-Omniscience AccuracySource | 19.9% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 81.6% | — | Not comparable |
| AA Openness IndexSource | 38.9% | — | Not comparable |
| MMLU-ReduxSource | — | 86.2% | Not comparable |
| GPQA-DSource | — | 57.6% | Not comparable |
Multimodal2 benchmarks
Frequently Asked Questions (2)
Which is better, Gemma 4 31B or Mellum2-12B-A2.5B-Thinking?
Gemma 4 31B and Mellum2-12B-A2.5B-Thinking are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, Gemma 4 31B or Mellum2-12B-A2.5B-Thinking?
Mellum2-12B-A2.5B-Thinking has the edge for knowledge tasks in this comparison, averaging 57.6 versus 52.9. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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