Qwen3 32B vs Gemma 3 27B — the best 4-bit single-GPU local models right now. 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 | Qwen3 32B | Gemma 3 27B |
|---|---|---|
| Developer | Alibaba | |
| Type | LLM (dense) | LLM (multimodal) |
| Parameters | 32B | 27B |
| Context window | 128K | 128K |
| Modality | Text → Text | Text, Image → Text |
| License | Apache 2.0 (open) | Gemma (open) |
| Open weights | ✅ Yes | ✅ Yes |
| Input price ($/1M) | $0.08 | $0.08 |
| Output price ($/1M) | $0.28 | $0.16 |
| VRAM (4-bit) | ~20 GB | ~16 GB |
| Min GPU (local) | RTX 4090 24GB (Q4) | RTX 4080 16GB / RTX 4090 |
| Released | 2025 | 2025 |
Key differences
- Cost: Gemma 3 27B is 30% cheaper than Qwen3 32B 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 Qwen3 32B locally: ~~20 GB at 4-bit (min RTX 4090 24GB (Q4)).
- Run Gemma 3 27B locally: ~~16 GB at 4-bit (min RTX 4080 16GB / RTX 4090).
Which should you choose?
Choose Qwen3 32B if it fits your existing stack or you prefer Alibaba.
Choose Gemma 3 27B if you want the lower per-token cost for high-volume workloads.
→ 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.