Phi-4 Family — lokalny model AI od Microsoft
Autor: Jakub Rusinowski · Ostatnia aktualizacja:
Najnowszy model Microsoftu skupiony na treningu na wysokiej jakości danych syntetycznych. Phi-4 14B przewyższa w benchmarkach rozumowania wiele modeli dwukrotnie większych.
Warianty
Najmniejszy wariant Phi-4 Family potrzebuje około 9 GB VRAM przy Q4_K_M — skwantyzowane wagi plus narzut frameworka, bez pamięci podręcznej KV.
| Model | VRAM przy Q4 | VRAM | Kontekst | Uruchom |
|---|---|---|---|---|
| Phi-4 (14B) → 14B | ~9.3 GB | 16,000 | ollama run phi4 |
Pamięć to skwantyzowane wagi plus narzut przy Q4_K_M, liczone tym samym silnikiem co sprawdzarka GPU i VRAM.
Jak uruchomić Phi-4 Family lokalnie
Zainstaluj Ollama, a potem pobierz tag.
ollama run phi4Wybierz rozmiar powyżej, aby zobaczyć jego VRAM, szacowaną szybkość i polecenie instalacji.
Download Phi-4 Family — GGUF Quantizations
Pick a quantization and open it in LM Studio, Ollama, or Jan, or download the raw .gguf file directly. Quant list and sizes resolved from Hugging Face.
Phi-4 (14B) — GGUF quants · bartowski/phi-4-GGUF
| Quant | Size | Download (.gguf) |
|---|---|---|
| Q3_K_M | 5.97 GB (est.) | phi-4-Q3_K_M.gguf |
| Q4_K_M | 8.45 GB (est.) | phi-4-Q4_K_M.gguf |
| Q5_K_M | 9.92 GB (est.) | phi-4-Q5_K_M.gguf |
| Q6_K | 11.48 GB (est.) | phi-4-Q6_K.gguf |
| Q8_0 | 14.88 GB (est.) | phi-4-Q8_0.gguf |
Download in LM Studio: lms get bartowski/phi-4-GGUF
Want this model on your phone? You can run it on your desktop with LM Studio and chat from your iPhone or iPad over an encrypted link — see Run LM Studio Models on Your Phone (LM Link).
Licencja
Commercial use permitted. No usage restrictions beyond attribution.
Dotyczy: Phi-4 (14B)Polecane GPU
Najtańsze GPU z naszego katalogu, które uruchomi Phi-4 Family lokalnie (min. 9 GB VRAM), to Intel Arc B570 (10 GB).
Czy uruchomię Phi-4 Family na moim GPU?
- Phi-4 Family na AMD Radeon RX 7800 XT
- Phi-4 Family na AMD Radeon RX 7900 XT
- Phi-4 Family na AMD Radeon RX 9060 XT 16GB
- Phi-4 Family na AMD Radeon RX 9060 XT 8GB
- Phi-4 Family na AMD Radeon RX 9070
- Phi-4 Family na AMD Radeon RX 9070 XT
- Phi-4 Family na Apple M1
- Phi-4 Family na Intel Arc B570
- Phi-4 Family na Intel Arc B580
- Phi-4 Family na NVIDIA GeForce RTX 3060 (12GB)
- Phi-4 Family na NVIDIA GeForce RTX 3070
- Phi-4 Family na NVIDIA GeForce RTX 3070 Ti
- Phi-4 Family na NVIDIA GeForce RTX 3080 (10GB)
- Phi-4 Family na NVIDIA GeForce RTX 4060
- Phi-4 Family na NVIDIA GeForce RTX 4060 Ti 16GB
- Phi-4 Family na NVIDIA GeForce RTX 4070
- Phi-4 Family na NVIDIA GeForce RTX 4070 Super
- Phi-4 Family na NVIDIA GeForce RTX 4070 Ti
- Phi-4 Family na NVIDIA GeForce RTX 4070 Ti Super
- Phi-4 Family na NVIDIA GeForce RTX 4080
- Phi-4 Family na NVIDIA GeForce RTX 4080 Super
- Phi-4 Family na NVIDIA GeForce RTX 5060
- Phi-4 Family na NVIDIA GeForce RTX 5060 Ti 16GB
- Phi-4 Family na NVIDIA GeForce RTX 5060 Ti 8GB
- Phi-4 Family na NVIDIA GeForce RTX 5070
- Phi-4 Family na NVIDIA GeForce RTX 5070 Ti
- Phi-4 Family na NVIDIA GeForce RTX 5080
Phi-4 Family — najczęściej zadawane pytania
How much VRAM does Phi-4 Family need?
Phi-4 Family needs about 9 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Phi-4 (14B) (9 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Can I run Phi-4 Family on an RTX 4090 (24 GB)?
Yes — Phi-4 Family runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.
What quantization should I use for Phi-4 Family?
Q4_K_M is the best balance of quality and VRAM for Phi-4 Family in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
How do I run Phi-4 Family with Ollama?
Install Ollama, then run: ollama run phi4. This downloads Phi-4 Family and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.