Command R Family — Cohere 的本地 AI 模型

作者: Jakub Rusinowski · 最后更新:

更新的替代方案. Cohere 尚未在本库中发布更新的模型。如果你今天要选择,Mistral Small 4 是一个相当的当前选项。 查看 Mistral Small 4 →

专门针对RAG(检索增强生成)和工具使用优化的模型。Command R系列在引用来源和文档推理方面表现卓越。

变体

Command R Family 最小的变体在 Q4_K_M 下约需 22 GB 显存——量化权重加框架开销,不含 KV 缓存。

模型显存
Command R (35B) →
35B
~21.9 GB
Command R+ (104B) →
104B
~63.6 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 Command R Family

安装 Ollama,然后拉取标签。

ollama run command-r

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。

许可证

CC-BY-NC-4.0仅限研究/非商业用途

Research / non-commercial only — this licence does NOT permit shipping a commercial product.

适用于: Command R (35B), Command R+ (104B)

推荐 GPU

目录中能在本地运行 Command R Family(至少 22 GB 显存)的最便宜 GPU 是 NVIDIA GeForce RTX 5090 (32 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。
NVIDIA GeForce RTX 5090 32GB
32 GB VRAM · 575 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 Command R Family 吗?

Command R Family — 常见问题

How much VRAM does Command R Family need?

Command R Family needs about 22 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Command R (35B) (22 GB, Q4_K_M); Command R+ (104B) (64 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.

Can I run Command R Family on an RTX 4090 (24 GB)?

Yes — Command R 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 Command R Family?

Q4_K_M is the best balance of quality and VRAM for Command R 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 Command R Family with Ollama?

Install Ollama, then run: ollama run command-r. This downloads Command R Family and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.