Llama vs Mistral

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

功能对比

Llama 与 Mistral 功能对比
维度	Llama	Mistral
Context window	128k tokens	32k tokens
License	Llama Community License	Apache-2.0
Open weights	Yes	Yes
Parameters	8B, 70B, 405B	7B
Provider	Meta	Mistral AI

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 Mistral 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.

Mistral

model · Models

Mistral is an open-weight model family that emphasises quality per parameter rather than raw size, so a small model can run on modest hardware without collapsing in quality. It solves the cost problem for teams whose workload is not hard enough to justify a frontier model. It exists because most production tasks are narrow enough that a well-trained small model is sufficient, and serving one is an order of magnitude cheaper than calling a large hosted model.