Can RTX 4090 run Gemma 4 12B?
Yes. Measured 98.1 tok/s generation (llama.cpp, llama-bench tg128 (quant per result); source).
Every measured result for Gemma 4 12B on RTX 4090
| Build | Quant / setup | Engine | tok/s | |
|---|---|---|---|---|
| RTX 4090: 2026 models (llamabench community) | llama-bench tg128 (quant per result) | llama.cpp | 98.1 | source |
Memory: RTX 4090 has 24 GB. Gemma 4 12B weights are about 7.3 GB at Q4_K_M (11.91B params × 4.89 bits ÷ 8, before context/KV cache). Arithmetic, not a measurement; long contexts need more. Check other quants in the VRAM calculator.
Speeds are decode (generation) tokens/sec as reported by each source; quant, engine and context differ, so small gaps are noise.
All measured speeds for Gemma 4 12B: best home rig for Gemma 4 12B.
Gemma 4 12B on other hardware: RTX 3060 12GB · RTX 5070 Ti · RTX 5090
Other models measured on RTX 4090: Gemma 4 26B-A4B · Gemma 4 31B · LFM2.5 24B-A2B · Nemotron 3.5 Bolt 74B-A9B · Qwen3.5 9B · Qwen3.6 27B · gpt-oss 20B
Not enough VRAM? Rent before you buy. Run Gemma 4 12B on a bigger GPU on a rented 24–96 GB cloud GPU by the hour and see the real speed before spending €1,000+. Try it on RunPod
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