Gemma 4 (Google) vs MiniMax M2 / M2.5
Which one should you pick? Here's the full breakdown.
Gemma 4 (Google)
Google DeepMind's open-weights model family -- multimodal, 256K context, runs on edge devices
MiniMax M2 / M2.5
MiniMax's open-weights frontier -- first open model to match Claude Opus 4.6 on SWE-Bench at 10-20× lower cost
| Category | Gemma 4 (Google) | MiniMax M2 / M2.5 |
|---|---|---|
| Ease of Use | 7.0 | 6.5 |
| Output Quality | 8.0 | 9.0 |
| Value | 10.0 | 9.5 |
| Features | 8.0 | 8.5 |
| Overall | 8.3 | 8.4 |
Pricing Comparison
| Feature | Gemma 4 (Google) | MiniMax M2 / M2.5 |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0 |
Benchmark Head-to-Head
Gemma 4 31B vs MiniMax M2.5 (230B/10B active MoE)
| Benchmark | Gemma 4 (Google) | MiniMax M2 / M2.5 |
|---|---|---|
| GPQA Diamond | 84.3% | 76.8% |
| HumanEval | 85% | 91% |
Which Should You Pick?
Pick Gemma 4 (Google) if...
- ✓Stronger on graduate-level science questions (+7.5% on GPQA Diamond)
Developers and businesses who need a permissively licensed multimodal LLM they can self-host or fine-tune. Especially good for multilingual use cases and on-device deployment.
Visit Gemma 4 (Google)Pick MiniMax M2 / M2.5 if...
- ✓Higher output quality (9 vs 8)
- ✓Stronger on python code generation (+6.0% on HumanEval)
Agentic coding and tool-use workflows on a budget. Best price-to-SWE-Bench ratio of any open-weights model in 2026.
Visit MiniMax M2 / M2.5Our Verdict
Gemma 4 (Google) and MiniMax M2 / M2.5 are extremely close overall. Your choice comes down to specific needs -- Gemma 4 (Google) is better for developers and businesses who need a permissively licensed multimodal llm they can self-host or fine-tune, while MiniMax M2 / M2.5 works best for agentic coding and tool-use workflows on a budget.