What Models?

Pick the right model for your GPU — in seconds.

What GPU do you need to run Gemma 3 4B?

3.88B params 128K max context Vision

The smallest GPU memory that runs Gemma 3 4B well is 4 GB (Q4_K_M, e.g. T1000). 131 of 132 GPUs run it well.

MMLU 63

VRAM needed per quantization

QuantizationWeights16K context32K contextFull 128K
Q4_K_M2.5 GB2.8 GB3.1 GB4.9 GB
Q8_04.1 GB4.4 GB4.7 GB6.6 GB

Weights plus fp16 KV cache. Leave ~1 GB headroom for the inference engine.

Cheapest GPUs that can run Gemma 3 4B

Lowest launch MSRP among GPUs that run its smallest quantization (Q4_K_M) well, with at least 16K context.

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GPUs that can run Gemma 3 4B

Best quantization that fits on each GPU, with the context and speed it gets. For chips with several memory sizes, the smallest that works is shown.

NVIDIA

AMD

Intel

Apple

  • M1 8 GB Q8_0 128K context · ~13 tok/s
  • M2 8 GB Q8_0 128K context · ~19 tok/s
  • M3 8 GB Q8_0 128K context · ~19 tok/s
  • M1 Pro 16 GB Q8_0 128K context · ~39 tok/s
  • M2 Pro 16 GB Q8_0 128K context · ~39 tok/s
  • M4 16 GB Q8_0 128K context · ~23 tok/s
  • M5 16 GB Q8_0 128K context · ~30 tok/s
  • M6 16 GB Q8_0 128K context · ~30 tok/s
  • M3 Pro 18 GB Q8_0 128K context · ~29 tok/s
  • M4 Pro 24 GB Q8_0 128K context · ~53 tok/s
  • M5 Pro 24 GB Q8_0 128K context · ~60 tok/s
  • M1 Max 32 GB Q8_0 128K context · ~78 tok/s
  • M2 Max 32 GB Q8_0 128K context · ~78 tok/s
  • M3 Max 36 GB Q8_0 128K context · ~58 tok/s
  • M4 Max 36 GB Q8_0 128K context · ~80 tok/s
  • M5 Max 36 GB Q8_0 128K context · ~90 tok/s
  • M1 Ultra 64 GB Q8_0 128K context · ~156 tok/s
  • M2 Ultra 64 GB Q8_0 128K context · ~156 tok/s
  • M3 Ultra 96 GB Q8_0 128K context · ~160 tok/s
  • M5 Ultra 96 GB Q8_0 128K context · ~234 tok/s
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