Gemma 3 27B vs Llama 3.3 70B — Google’s efficient 27B versus Meta’s 70B. Below is the full side-by-side: specifications, API pricing, context window, local hardware requirements, and a clear, data-driven recommendation on which to pick.
| Spezifikation | Gemma 3 27B | Llama 3.3 70B |
|---|---|---|
| Entwickler | Meta | |
| Typ | LLM (multimodal) | LLM (dicht) |
| Parameter | 27 Mrd. | 70B |
| Kontextfenster | 128K | 128K |
| Modalität | Text, Bild → Text | Text → Text |
| Lizenz | Gemma (offen) | Llama 3.3 Community (offen) |
| Offene Gewichte | ✅ Ja | ✅ Ja |
| Input price ($/1M) | $0.08 | $0.10 |
| Output price ($/1M) | $0.16 | $0.32 |
| VRAM (4-Bit) | ca. 16 GB | ca. 40 GB |
| Min GPU (local) | RTX 4080 16 GB / RTX 4090 | 2× RTX 4090 / 1× 48 GB |
| Veröffentlicht | 2025 | 2024 |
Key differences
- Kosten: Gemma 3 27B is 55% cheaper than Llama 3.3 70B on a blended-token basis.
- Offenheit: both are open-weight, so either can be self-hosted or fine-tuned. Compare their VRAM needs above to see what your GPU can run.
- Run Gemma 3 27B locally: ~~16 GB at 4-bit (min RTX 4080 16GB / RTX 4090).
- Run Llama 3.3 70B locally: ~~40 GB at 4-bit (min 2× RTX 4090 / 1× 48GB).
Welches Modell sollten Sie wählen?
Choose Gemma 3 27B if you want the lower per-token cost for high-volume workloads.
Choose Llama 3.3 70B if it fits your existing stack or you prefer Meta.
→ Estimate real costs in the API cost calculator · check local hardware in the VRAM-Rechner · browse all 30+ models.
All specs and prices are pulled live from our Datenbank für KI-Modelle and kept current. Compare either model against others, or estimate your own monthly spend with the free calculators above.