Phi vs Gemma
Phi and Gemma side by side: model sizes, the VRAM you need, context window, abilities, licence and which one to pick.
Side by side
| Phi | Gemma | |
|---|---|---|
| Type | Open-weight models | Open-weight models |
| Developer | Microsoft | Google DeepMind |
| Newest model | Phi-4-reasoning · Apr 2025 | Gemma 4 · Mar 2026 |
| Sizes | 3.8B · 14B | 4B · E2B · E4B · 12B · 27B · 26B · 31B |
| Smallest VRAM (4-bit) | ~3.5 GB (Phi-4-mini 3.8B) | ~4.5 GB (TranslateGemma 4B) |
| Context window | 128K tokens | 256K tokens |
| Abilities | Tool calling | Tool callingReasoning modeImage inputAudio input |
| Licence | MIT | Apache 2.0, Gemma Terms of Use, Health AI Developer Foundations |
| Run it | ollama run phi4-mini:3.8b | ollama run translategemma:4b |
Which one should you pick?
- Phi runs on smaller hardware: from ~3.5 GB of GPU memory, against ~4.5 GB.
- Gemma reads longer inputs: a 256K-token context window.
- Only Gemma has image input.
- Only Gemma has a reasoning mode.
- Only Gemma has audio input.
Pick Phi if…
- you need maths or logic from a small model
- you want an MIT-licensed model from Microsoft
Pick Gemma if…
- you need image or audio input on small hardware
- you want Google-quality models under Apache 2.0
- you are building on-device or laptop AI
VRAM and download size
Ollama's default 4-bit builds with an 8K context. Read GB as system RAM on a CPU-only machine or a Mac.
Phi
| Model | Download | VRAM |
|---|---|---|
| Phi-4-mini 3.8B | 2.5 GB | ~3.5 GB |
| Phi-4-mini-reasoning 3.8B | 3.2 GB | ~4.5 GB |
| Phi-4 14B | 9.1 GB | ~11 GB |
| Phi-4-reasoning 14B | 11 GB | ~13 GB |
Gemma
| Model | Download | VRAM |
|---|---|---|
| TranslateGemma 4B | 3.3 GB | ~4.5 GB |
| MedGemma 4B | 3.3 GB | ~4.5 GB |
| Gemma 4 E2B | 4.6 GB | ~6 GB |
| Gemma 4 E4B | 6.6 GB | ~8 GB |
| Gemma 4 12B | 8 GB | ~9.5 GB |
| TranslateGemma 12B | 8.1 GB | ~9.5 GB |
| TranslateGemma 27B | 17 GB | ~19.5 GB |
| MedGemma 27B | 17 GB | ~19.5 GB |
| Gemma 4 26B | 19 GB | ~21.5 GB |
| Gemma 4 31B | 20 GB | ~22.5 GB |
Frequently asked questions
Is Phi better than Gemma?
It depends on the job and your hardware. Phi runs on smaller hardware: from ~3.5 GB of GPU memory, against ~4.5 GB. Gemma reads longer inputs: a 256K-token context window. Only Gemma has image input. For quality, test both on your own prompts: benchmark rankings change with every release.
Which needs less VRAM, Phi or Gemma?
Phi starts at ~3.5 GB (2.5 GB download). Gemma starts at ~4.5 GB (3.3 GB download).
Can I use Phi and Gemma commercially?
Phi: MIT. Gemma: Apache 2.0, Gemma Terms of Use, Health AI Developer Foundations. Check the exact licence of the model you deploy; custom licences can limit very large companies or certain uses.
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