Lmstudio-community
gemma 3 4b it (4B parameters) requires approximately 4.7 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 6 GB of VRAM.
Quick specs
Related models
Quick picks
Best hardware
Run this model
Quantization options
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.6 GB | Low | — |
Q3_K_S | 3 | 2.0 GB | Low | — |
NVFP4 | 4 | 2.2 GB | Medium | — |
Q4_K_M | 4 | 2.4 GB | Medium | — |
Q5_K_M | 5 | 2.9 GB | High | — |
Q6_K | 6 | 3.3 GB | High | — |
Q8_0 | 8 | 4.3 GB | Very High | — |
F16 | 16 | 8.2 GB | Maximum | — |
Hardware compatibility
Computing compatibility...
Memory breakdown
Frequently asked questions
gemma 3 4b it (4B parameters) requires approximately 4.7 GB of VRAM with Q4_K_M quantization. Lower quantizations like Q4_K_M use less memory but may reduce quality.
Yes, Intel Arc A380 6GB can run gemma 3 4b it with a compatibility score of 54/100. It provides 6 GB of memory and achieves approximately 37.4 tokens per second.
The recommended quantization for gemma 3 4b it is Q4_K_M, which offers the best balance between model quality and memory efficiency. Higher quantizations preserve more quality but require more VRAM.
The top recommended hardware for gemma 3 4b it: RTX 2060 6GB (score: 55/100), RTX 4050 Laptop 6GB (score: 55/100), GTX 1660 Super 6GB (score: 55/100). These provide the best combination of memory, bandwidth, and compute for running this model locally.
Yes, gemma 3 4b it is well-suited for chat. It was designed with these use cases in mind.
See also
