Two of the most capable open AI models launched in early 2026: Google's Gemma 4 and Meta's Llama 4 Maverick. Both are free, both are powerful — but they serve different use cases. Here's how they compare.
Quick Comparison
| Feature | Gemma 4 (31B) | Llama 4 Maverick (400B) |
|---|---|---|
| Developer | Google DeepMind | Meta AI |
| Parameters | 2B / 4B / 26B / 31B | 400B (MoE) |
| Context Window | 256K tokens | 10M tokens |
| Multimodal | Text + Image + Audio + Video | Text + Image |
| Languages | 140+ languages | 12 languages |
| License | Apache 2.0 | Llama License |
| On-device | Yes (2B runs on phone) | No (too large) |
| Function Calling | Native | Native |
Where Gemma 4 Wins
1. Edge and Mobile Deployment
Gemma 4's biggest advantage is its range of model sizes. The E2B (2B) model runs on a smartphone, the E4B (4B) on a laptop — no GPU needed. Llama 4 Maverick at 400B parameters requires serious server hardware.
2. Multimodal Breadth
Gemma 4 natively processes text, images, audio, and video. Llama 4 handles text and images but lacks native audio and video understanding.
3. Language Coverage
With 140+ languages built-in, Gemma 4 is far more globally accessible. Llama 4 supports 12 languages — enough for major markets but limited for global applications.
4. Licensing Freedom
Apache 2.0 means no restrictions whatsoever. Llama 4's license has commercial use limitations for companies with 700M+ monthly active users.
Where Llama 4 Wins
1. Raw Power
At 400B parameters with MoE architecture, Llama 4 Maverick is simply a larger, more capable model for complex reasoning tasks when you have the hardware.
2. Context Length
10M token context window vs Gemma 4's 256K. For processing extremely long documents or codebases, Llama 4 has a clear edge.
3. Ecosystem Maturity
Meta's Llama series has been around since 2023. The ecosystem of tools, fine-tunes, and community resources is more mature.
Benchmark Comparison
Based on published benchmarks (April 2026):
| Benchmark | Gemma 4 31B | Llama 4 Maverick |
|---|---|---|
| MMLU | Strong | Strong |
| HumanEval (Coding) | Competitive | Competitive |
| ARC-AGI-2 | 77.1% (Gemini 3.1 Pro) | - |
| Math | Improved over Gemma 3 | Strong |
Note: Direct head-to-head benchmarks vary by task. Neither model dominates across all benchmarks.
Which Should You Choose?
Choose Gemma 4 if:
- You need to run AI on phones, laptops, or edge devices
- You need multimodal input (especially audio/video)
- You're building for a global, multilingual audience
- You want zero licensing restrictions (Apache 2.0)
- You want the fastest path from download to running
Choose Llama 4 if:
- You have powerful GPU servers available
- You need maximum reasoning capability for complex tasks
- You need extremely long context (10M tokens)
- You're already invested in the Llama ecosystem
Can You Run Both?
Yes! Many developers use both:
- Gemma 4 E4B for local development and testing (fast, low resources)
- Llama 4 Maverick on cloud servers for production heavy-lifting
Both models are available through Ollama, making it easy to switch between them.
Bottom Line
Gemma 4 is the best open model you can run on your own hardware. Its range of model sizes, multimodal capabilities, and Apache 2.0 license make it the most versatile choice for most developers.
Llama 4 is the most powerful open model period — but you need the hardware to match.
For most individual developers and small teams, Gemma 4 is the practical choice. For organizations with GPU clusters, Llama 4 unlocks higher ceilings.
Both models are freely available. Try Gemma 4 with one command: ollama run gemma4
