Compare / Gemma 4 12B vs Mellum2 12B-A2.5B Instruct
Gemma 4 12B vs Mellum2 12B-A2.5B Instruct
Updated November 2026
Verdict
Gemma 4 12B scores higher on the Small LM Index: 58.4 vs 39.2. On the 3 benchmarks both labs report, Gemma 4 12B wins 3 and Mellum2 12B-A2.5B Instruct wins 0. Both need about 8.9 GB of memory at 4-bit quantization. Neither model has a hosted API on OpenRouter, so you would run both yourself.
Pick Gemma 4 12B if…
- you want the strongest model overall
- you mostly write code
- you need math and reasoning
- you work with long documents
- you need image input
- you want the more widely used model (more quantized builds and community support)
Pick Mellum2 12B-A2.5B Instruct if…
No clear advantage in the data we have.
Specifications
| Gemma 4 12B | Mellum2 12B-A2.5B Instruct | |
|---|---|---|
| Small LM Index | 58.4 (likely 56–61) | 39.2 (likely 36–42) |
| Lab | Google · United States | JetBrains (Mellum) · Europe |
| Released | 2026-06-03 | 2026-06-01 |
| Parameters | 11.9B (dense) | 12.2B (2.5B active, MoE) |
| Memory at 4-bit | ~8.9 GB | ~8.3 GB |
| Context window | 256K tokens | 131K tokens |
| Input | text, image, audio | text |
| Reasoning | Hybrid (thinking on/off) | No thinking |
| License | Apache-2.0 | Apache-2.0 |
| API price / 1M tokens | Self-host only | Self-host only |
| Hugging Face downloads (30 days) | 1.8M | 11.1K |
Benchmarks
Higher is better. Bold marks the winner where both labs report a score. ≈ marks the index model's estimate for a score that wasn't reported, ✓ an independent measurement and * a score measured by another lab.
| Benchmark | Gemma 4 12B | Mellum2 12B-A2.5B Instruct |
|---|---|---|
| MMLU-Pro Knowledge | 77.2 | ≈ 62 |
| GPQA Diamond Knowledge | 75.3✓ | 40.9 |
| Humanity's Last Exam Reasoning | 15.7✓ | ≈ 6 |
| AIME Math | 77.5 | 41.7 |
| LiveCodeBench Coding | 72.0 | 37.2 |
| τ²-Bench Agentic | 36.3✓ | — |
| IFBench Instruction following | 73.5✓ | — |
| MMMU-Pro Vision | 69.1 | — |
| MMLU Knowledge | — | 78.1 |
| IFEval Instruction following | — | 75.8 |
| BFCL Agentic | — | 44.2 |
| AA-LCR Long context | 63.7✓ | — |
Scores are mostly reported by each lab with its own settings, so small gaps are noise. See the methodology. Open in the interactive comparison to add more models.
Questions
Which is better, Gemma 4 12B or Mellum2 12B-A2.5B Instruct?
Gemma 4 12B scores higher on the Small LM Index: 58.4 vs 39.2. On the 3 benchmarks both labs report, Gemma 4 12B wins 3 and Mellum2 12B-A2.5B Instruct wins 0.
Which is cheaper to run?
Neither model has a hosted API on OpenRouter, so you would run both yourself. Both need about 8.9 GB of memory at 4-bit quantization.
Which has the longer context window?
Gemma 4 12B has the longer context window: 256K tokens against 131K.
Can I use Gemma 4 12B and Mellum2 12B-A2.5B Instruct commercially?
Both are released under the Apache-2.0 license. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.