Llama vs Phi

Open-weight language model family from Meta, released for local and self-hosted use.

功能对比

Llama 与 Phi 功能对比
维度	Llama	Phi
Context window	128k tokens	128k tokens
License	Llama Community License	MIT
Open weights	Yes	Yes
Parameters	8B, 70B, 405B	3.8B, 14B
Provider	Meta	Microsoft

灰底行表示两者相同；有差异的行才是下方推荐结论的依据。

该选哪个？

由上述差异按固定规则生成，不是模型生成的。

Choose Llama if…

已记录的属性中，没有任何一项显示它更有优势。

Choose Phi if…

已记录的属性中，没有任何一项显示它更有优势。

Llama

model · Models

Llama is a family of language models whose weights are published, so they can be run on your own hardware instead of only through an API. It solves the problem that most capable models are reachable only as a hosted service, which rules them out when data cannot leave your network or when per-token cost dominates. It exists because releasing weights turned out to build an ecosystem of fine-tunes and tooling around one architecture, and it is the model most local inference tools target first.

Phi

model · Models

Phi is a family of small language models trained on a deliberately narrow, high-quality corpus of textbooks and exercises rather than on a web-scale crawl. It solves the assumption that capability requires scale, showing that data selection can substitute for a large part of it. It exists because it reframes the question from how much data to what kind of data, and the answer is useful when the budget is a single GPU.