Phi-4 Family — Microsoft 的本地 AI 模型

作者: Jakub Rusinowski · 最后更新:

微软最新专注于高质量合成数据训练的模型。Phi-4 14B在推理基准测试中超越许多两倍大小的模型。

变体

Phi-4 Family 最小的变体在 Q4_K_M 下约需 9 GB 显存——量化权重加框架开销,不含 KV 缓存。

模型显存
Phi-4 (14B) →
14B
~9.3 GB

显存为 Q4_K_M 下的量化权重加开销,与 GPU 与显存检测器使用同一引擎计算。

如何在本地运行 Phi-4 Family

安装 Ollama,然后拉取标签。

ollama run phi4

在上方选择一个尺寸,查看它自己的显存、速度估算和安装命令。

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

QuantSizeDownload (.gguf)
Q3_K_M5.97 GB (est.)phi-4-Q3_K_M.gguf
Q4_K_M8.45 GB (est.)phi-4-Q4_K_M.gguf
Q5_K_M9.92 GB (est.)phi-4-Q5_K_M.gguf
Q6_K11.48 GB (est.)phi-4-Q6_K.gguf
Q8_014.88 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).

许可证

MIT允许商业使用

Commercial use permitted. No usage restrictions beyond attribution.

适用于: Phi-4 (14B)

推荐 GPU

目录中能在本地运行 Phi-4 Family(至少 9 GB 显存)的最便宜 GPU 是 Intel Arc B570 (10 GB).

联盟营销声明: 本页部分链接为联盟推广链接——如果你通过它们购买,LLM Configurator 可能会获得佣金,而你无需支付任何额外费用。作为亚马逊联盟成员(Amazon Associate),LLM Configurator 会从符合条件的购买中获得收益。
Intel Arc B570 10GB
10 GB VRAM · 150 W board power
2026年价格波动较大——请以当前商品页价格为准。

我的 GPU 能运行 Phi-4 Family 吗?

Phi-4 Family — 常见问题

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.