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Models / Gemma 4 12B / VRAM

How much VRAM do you need for Gemma 4 12B?

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Weight math from the model card, plus every measured RigBase result for Gemma 4 12B. Leave extra room for context (KV cache).

Quick answer: at Q4_K_M the weights are about 7.3 GB (11.91B params × 4.89 bits ÷ 8, llama.cpp quantize table). the smallest-memory build with a measured result here is RTX 3060 (12 GB) at 38.5 tok/s. fastest plain decode: 142 tok/s on RTX 5090. Open the VRAM calculator →

Weight size by quant

QuantBits/weightWeights only
Q8_08.5012.7 GB
Q6_K6.569.8 GB
Q5_K_M5.708.5 GB
Q4_K_M4.897.3 GB
Q3_K_M4.005.9 GB
Q2_K3.164.7 GB

Bits-per-weight for GGUF rows: llama.cpp quantize README. Parameter count: GGUF param count via llamabench.ai. We advise staying at Q4 or above for chat quality — see Is Q4 good enough?.

Measured speeds for Gemma 4 12B

HardwareQuantEnginetok/s
RTX 5090 · 32 GBllama-bench tg128 (quant per result)llama.cpp142
RTX 4090 · 24 GBllama-bench tg128 (quant per result)llama.cpp98.1
RTX 4090 · 24 GBQAT Q4_0llama.cpp b893197.7
RTX 5070 Ti · 16 GBllama-bench tg128 (quant per result)llama.cpp87.6
RTX 3060 · 12 GBllama-bench tg128 (quant per result)llama.cpp38.5
Apple M6 (12-core GPU, unified) · 32 GBQAT (google/gemma-4-12b-qat)LM Studio18.2

⚡ = speculative decoding (MTP, DFlash…). Full list: best home rig for Gemma 4 12B.

Related

All Gemma 4 12B builds VRAM + KV calculator By VRAM size GGUF vs AWQ vs FP8 vs NVFP4 How much system RAM?

FAQ

How much VRAM do you need for Gemma 4 12B?

Weights alone are about 7.3 GB at Q4_K_M (11.91B × 4.89 bits ÷ 8). Add memory for the KV cache (context) and the runtime. The smallest-memory measured result in RigBase is 12 GB (RTX 3060) at 38.5 tok/s. Going below Q4 usually hurts quality for chat; see the Q4 guide.

What is the fastest measured speed for Gemma 4 12B?

RTX 5090: 142 tok/s plain decode (llama-bench tg128 (quant per result), llama.cpp).

Does system RAM replace VRAM?

Only for overflow. When the whole model fits in GPU or unified memory, system RAM barely matters for decode speed. See the system-RAM guide.

Not enough VRAM? Rent before you buy. Run Gemma 4 12B on a rented 24–96 GB cloud GPU by the hour and see the real speed before spending €1,000+. Try it on Runpod
Referral link: if you sign up with Google and add $10, Runpod gives you and RigBase bonus credit (terms). It never affects our data.