Models › Gemma 4 12B › RTX 3090
Can I run Gemma 4 12B on RTX 3090?
Yes
Yes. Gemma 4 12B fits fully on the RTX 3090 at Q8_0 (about 14.8 GB of 24 GB usable, 8k context). ESTIMATE
Verdict by quantization (8k context, f16 KV, 32 GB RAM for offload)
| Quant | Needs | RTX 3090 (24 GB) |
|---|---|---|
| Q3_K_M | 7.8 GB | ✅ Fits |
| IQ4_XS | 8.1 GB | ✅ Fits |
| Q4_K_M | 9.1 GB | ✅ Fits |
| MXFP4 | 8.7 GB | ✅ Fits |
| Q5_K_M | 10.4 GB | ✅ Fits |
| Q6_K | 11.8 GB | ✅ Fits |
| Q8_0 | 14.8 GB | ✅ Fits |
| F16 | 26.6 GB | 🐢 Needs RAM offload |
Speed ESTIMATE
About 83–86 tok/s generation at Q4_K_M, scaled from measured Llama 2 7B Q4_0 runs on this chip. Not measured for Gemma 4 12B; submit a benchmark.
Memory figures are estimates from the model's parameter count and config.json (Hugging Face). How we calculate. Last verified with data from 2026-10-20.
FAQ
Can I run Gemma 4 12B on the RTX 3090?
Yes. Gemma 4 12B fits fully on the RTX 3090 at Q8_0 (about 14.8 GB of 24 GB usable, 8k context).
How much VRAM does Gemma 4 12B need?
About 9.1 GB at Q4_K_M and 14.8 GB at Q8_0 with 8k context (estimate).
Gemma 4 12B on other hardware: RTX 3060 12GB · RTX 4060 Ti 16GB · RTX 5060 Ti 16GB · RTX 5090 · Apple M4 Pro (48 GB)
Other models on RTX 3090: gpt-oss 20B (MoE) · Qwen3.6 27B · Qwen3.6 35B A3B (MoE) · Qwen3.8 27B · Gemma 4 31B · Gemma 4 26B A4B (MoE) · Qwen3.5 9B · Qwen3 Coder 30B A3B (MoE) · GLM 4.7 Flash · Llama 3.1 8B Instruct
See all models for 24 GB VRAM.
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