Side-by-side comparison of Gemma 4 E4B Instruct (Google DeepMind · United States) and Llama 3.1 Nemotron 70B (NVIDIA · USA) for self-hosted deployment of the open-weight model. Gemma 4 E4B Instruct is rated conditional; Llama 3.1 Nemotron 70B is conditional. They part ways on licence: Gemma 4 E4B Instruct is "Apache 2.0", Llama 3.1 Nemotron 70B is "Llama community".
| Field | ||
|---|---|---|
| Summary | ||
| Verdict | Conditional Based on published licence terms, Gemma 4 E4B is an edge-optimised multimodal variant under pure Apache 2.0 with no prohibited-use carve-outs. Audio input (30s) and on-device deployment push GDPR biometric, AI Act emotion-recognition, and Art. 25 data-protection-by-design obligations entirely onto the integrator with no Google-side telemetry or kill-switch. | Conditional NVIDIA's Llama 3.1 fine-tune with custom RLHF. Inherits Llama 3.1 Community License terms. Strong conversational quality; useful default when you want Llama behaviour with NVIDIA's alignment. |
| Last reviewed | 2026-04-17 | 2026-04-15 |
| Open-weight | ||
| Licence | Apache 2.0 | Llama community |
| Commercial use | Unrestricted | With caps |
| Training data | Domain-level summary | Partial |
| Origin | United States | USA |
| Performance & pricing? | ||
| Quality index | 15/100 | 13/100 |
| Speed | — | 42 tok/s |
| Blended price | — | $1.20/M |
| Context window | — | — |
| Evidence | ||
| Sources | ||
No overlapping sources between the two entries.