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.
| Spec | Gemma 3 27B | Llama 3.3 70B |
|---|---|---|
| Developer | Meta | |
| Type | LLM (multimodal) | LLM (dense) |
| Parameters | 27B | 70B |
| Context window | 128K | 128K |
| Modality | Text, Image → Text | Text → Text |
| License | Gemma (open) | Llama 3.3 Community (open) |
| Open weights | ✅ Yes | ✅ Yes |
| Input price ($/1M) | $0.08 | $0.10 |
| Output price ($/1M) | $0.16 | $0.32 |
| VRAM (4-bit) | ~16 GB | ~40 GB |
| Min GPU (local) | RTX 4080 16GB / RTX 4090 | 2× RTX 4090 / 1× 48GB |
| Released | 2025 | 2024 |
Key differences
- Cost: Gemma 3 27B is 55% cheaper than Llama 3.3 70B on a blended-token basis.
- Openness: 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).
Which should you choose?
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 calculator · browse all 30+ models.
All specs and prices are pulled live from our AI models database and kept current. Compare either model against others, or estimate your own monthly spend with the free calculators above.