Gemma 3 4B vs Phi-3.5 Mini (3.8B)
Size, context window, license, approximate VRAM and the minimum local hardware each model needs — computed from our catalog and compatibility engine, not benchmarks.
| Gemma 3 4B | Phi-3.5 Mini (3.8B) | |
|---|---|---|
| Parameters | 4B | 3.8B |
| Context window | 128K tokens | 128K tokens |
| License | Gemma Terms of Use | MIT |
| ~VRAM @ 4-bit (Q4_K_M) | ~3 GB | ~2.5 GB |
| ~VRAM @ 8-bit (Q8_0) | ~4.5 GB | ~4 GB |
| Minimum device | NVIDIA GeForce RTX 3060 12GB | NVIDIA GeForce RTX 3060 12GB |
| Recommended device | Supermicro 8x H100 SuperServer | Supermicro 8x H100 SuperServer |
| Deployment | Local / on-prem | Local / on-prem |
| Capabilities | Vision, Multilingual, Long context | Reasoning, Long context, Multilingual |
Highlighted cells mark the lighter / longer / more permissive side per row, for local deployment. Informational rows have no winner.
Bottom line
Phi-3.5 Mini (3.8B) (~3.8B) is lighter than Gemma 3 4B (~4B), so it runs on more modest hardware, while Gemma 3 4B trades a larger footprint for more capacity. At 4-bit, Phi-3.5 Mini (3.8B) needs about 2.5GB versus ~3GB, a meaningful gap when choosing a GPU. Both target a 128K context window. Phi-3.5 Mini (3.8B)'s MIT license is the more permissive of the two for commercial use. Both can start on a NVIDIA GeForce RTX 3060 12GB-class machine. Figures are approximate working-set estimates, not benchmarks — verify the exact release before committing hardware.
Pick Gemma 3 4B if you have the memory to spare and want the larger model.
Pick Phi-3.5 Mini (3.8B) if you want the lighter footprint and cheaper hardware, or you want the more permissive MIT license.
8GB GPUs, a Mac mini, or a small mini PC at 4-bit. A current small generalist with a long context and image input.
8GB GPUs, a Mac mini, or even a strong CPU. A small reasoning-leaning model with a permissive MIT license.
Run the winner on hardware you control
Pick the model that fits your footprint, then turn the right machine into a private AI Business OS — no per-seat data leaving your premises.