Compare / Gemma 4 E4B vs Llama 3.1 8B
Gemma 4 E4B vs Llama 3.1 8B
Updated November 2026
Verdict
Gemma 4 E4B scores higher on the Small LM Index: 38.2 vs 21.3. On the 2 benchmarks both labs report, Gemma 4 E4B wins 2 and Llama 3.1 8B wins 0. Both need about 6.6 GB of memory at 4-bit quantization. Only Llama 3.1 8B has a hosted API on OpenRouter ($0.025 per million tokens); the other has to be self-hosted.
Pick Gemma 4 E4B if…
- you want the strongest model overall
- you need a permissive license (Apache-2.0)
- you need image input
Pick Llama 3.1 8B if…
- you want a hosted API rather than running it yourself
Specifications
| Gemma 4 E4B | Llama 3.1 8B | |
|---|---|---|
| Small LM Index | 38.2 (likely 34–42) | 21.3 (likely 15–29) |
| Lab | Google · United States | Meta · United States |
| Released | 2026-04-02 | 2024-07-23 |
| Parameters | 8B (dense) | 8B (dense) |
| Memory at 4-bit | ~5.6 GB | ~6.6 GB |
| Context window | 128K tokens | 128K tokens |
| Input | text, image, audio | text |
| Reasoning | Hybrid (thinking on/off) | No thinking |
| License | Apache-2.0 | Llama 3.1 Community |
| API price / 1M tokens | Self-host only | $0.025 ($0.020 in, $0.040 out) |
| Hugging Face downloads (30 days) | 4.1M | 4.5M |
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 E4B | Llama 3.1 8B |
|---|---|---|
| MMLU-Pro Knowledge | 69.4 | 48.3 |
| GPQA Diamond Knowledge | 58.6 | 30.4 |
| AIME Math | 42.5 | ≈ 18 |
| LiveCodeBench Coding | 52.0 | ≈ 21 |
| τ²-Bench Agentic | 42.2 | — |
| MMMU-Pro Vision | 52.6 | — |
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 E4B or Llama 3.1 8B?
Gemma 4 E4B scores higher on the Small LM Index: 38.2 vs 21.3. On the 2 benchmarks both labs report, Gemma 4 E4B wins 2 and Llama 3.1 8B wins 0.
Which is cheaper to run?
Only Llama 3.1 8B has a hosted API on OpenRouter ($0.025 per million tokens); the other has to be self-hosted. Both need about 6.6 GB of memory at 4-bit quantization.
Which has the longer context window?
Both have a 128K-token context window.
Can I use Gemma 4 E4B and Llama 3.1 8B commercially?
Gemma 4 E4B is released under Apache-2.0 and Llama 3.1 8B under Llama 3.1 Community. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.