Phi-4 Reasoning Mini 4B
Phi-4 reasoning at the edge tier. 3.8B with reasoning-token emission. The right pick when reasoning matters AND edge deployment is required.
Overview
Phi-4 reasoning at the edge tier. 3.8B with reasoning-token emission. The right pick when reasoning matters AND edge deployment is required.
Family & lineage
How this model relates to others in its lineage. Family members share architecture and training-data roots; parent / children edges record direct distillation or fine-tune relationships.
Strengths
- Reasoning at edge tier
- MIT license
Weaknesses
- 3.8B ceiling on reasoning depth
Quantization variants
Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.
| Quantization | File size | VRAM required |
|---|---|---|
| Q4_K_M | 2.4 GB | 4 GB |
Get the model
HuggingFace
Original weights
Source repository — direct quantization required.
Hardware that runs this
Cards with enough VRAM for at least one quantization of Phi-4 Reasoning Mini 4B.
Models worth comparing
Same parameter band, plus what's one tier above and below — so you can decide what actually fits your hardware.
Frequently asked
What's the minimum VRAM to run Phi-4 Reasoning Mini 4B?
Can I use Phi-4 Reasoning Mini 4B commercially?
What's the context length of Phi-4 Reasoning Mini 4B?
Source: huggingface.co/microsoft/Phi-4-reasoning-mini-4B
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