Phi-4 14B
Microsoft · Phi
Microsoft's research-driven Phi-4 focuses on synthetic high-quality training data, producing a 14B model that outperforms much larger models on coding and mathematical reasoning benchmarks. MIT licensed with zero usage restrictions for commercial projects.
Params
14B
License
MIT
Context
16K
Min VRAM
8 GB
Min RAM
16 GB
Tier
Standard
Run locally with Ollama
ollama run phi4:14bOnce running, Ollama exposes an OpenAI-compatible endpoint at localhost:11434/v1.
Will it run on my hardware?
Phi-4 14B needs about 8 GB of fast memory at Q4. Here is what in our hardware database clears that bar.
Runs at full speed · 12
Runs, but slower on shared memory · 3
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Specifications
| Parameters | 14B |
|---|---|
| Context window | 16K |
| License | MIT |
| Min VRAM (Q4) | 8 GB |
| Min RAM | 16 GB |
| Recommended tier | Standard |
| Best for | codinganalysisreasoning |
Variants on Ollama
Ollama serves the Q4_K_M quantization by default. Higher-precision tags exist for users with more memory.
Phi-4 14B
ollama run phi4:14bollama pull phi4:q8_0ollama pull phi4:fp16Exact quantization tags vary per model — run ollama show phi4 or check the tags page for the full list.
Popularity trend (illustrative)
Illustrative adoption trend, not actual download counts. We do not publish a download number for any model because we have no honest source for it.
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