Can I run Mistral Small 4 119B?

Mistral Small 4 119B is the odd one in this family: "small" in the name, but it carries 119B parameters total as a mixture-of-experts that activates only 6.5B per token. That design is why it punches above its active size for speed, but you still pay for the whole model in memory. At 4-bit it lands around 72 GB, and you need roughly 96 GB of RAM to hold it. No consumer GPU fits this one: a 12 GB RTX 3060 and even a 24 GB RTX 4090 are both out. This is a workstation or large unified-memory machine model, not a laptop pick.

In daily use the MoE trick pays off where it matters. On a high-memory Apple M Max it runs near 88 tokens per second, which feels conversational for a model this large, and even on CPU with DDR5 you get around 13 tokens per second if you are patient. The 256K context is generous on paper, but watch the memory: at 128K context the total footprint climbs to about 128.6 GB, so the long window is real only if you have the RAM to back it. Treat the full context as a hardware budget question, not a free setting.

Against its own lineage, Mistral 7B and Nemo 12B are the lightweight chat-only options if you cannot feed 96 GB; this model generally pulls ahead on reasoning, coding, and vision, which those two do not handle at all. Its closest peer here is Nemotron 3 Super 120B-A12B, another large MoE in the same weight class; the two tend to trade blows rather than one clearly leading. The standout is that you get a four-task model (chat, reasoning, coding, vision) under a true Apache 2.0 license, so commercial and production use are fully allowed with no provider strings attached.