Llama 3.2 3B 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.
| Llama 3.2 3B | Phi-3.5 Mini (3.8B) | |
|---|---|---|
| Parameters | 3B | 3.8B |
| Context window | 128K tokens | 128K tokens |
| License | Llama Community License | MIT |
| ~VRAM @ 4-bit (Q4_K_M) | ~2.5 GB | ~2.5 GB |
| ~VRAM @ 8-bit (Q8_0) | ~4 GB | ~4 GB |
| Minimum device | NVIDIA GeForce RTX 3060 12GB | NVIDIA GeForce RTX 3060 12GB |
| Recommended device | NVIDIA B200 (placeholder) | NVIDIA B200 (placeholder) |
| Deployment | Local / on-prem | Local / on-prem |
| Capabilities | Tools, 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
Llama 3.2 3B (~3B) is lighter than Phi-3.5 Mini (3.8B) (~3.8B), so it runs on more modest hardware, while Phi-3.5 Mini (3.8B) trades a larger footprint for more capacity. 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 Llama 3.2 3B if you want the lighter footprint and cheaper hardware.
Pick Phi-3.5 Mini (3.8B) if you have the memory to spare and want the larger model, or you want the more permissive MIT license.
Comfortable on any 8GB GPU, a Mac mini, or a small mini PC. A good entry assistant for a single office.
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.
Get started