Can I run Qwen 3.5 122B-A10B?

Qwen 3.5 122B-A10B is a big mixture-of-experts model for people who want frontier-style chat, reasoning, coding, and vision on their own hardware. The MoE design is the whole story: of its 122B total parameters, only 10B activate per token, so it generates far faster than a dense model this large would. The catch is memory, because you still have to hold the entire model resident. At a 4-bit quant that is about 74 GB, and you need roughly 96 GB of RAM to load it at all. In practice that means a high-memory workstation or an Apple Silicon Mac with a lot of unified memory; it does not fit on a 24 GB RTX 4090, let alone a 12 GB card.

Where it does fit, it feels surprisingly quick for its size thanks to those 10B active parameters. On an M Max you can expect around 57 tokens per second, fast enough to read comfortably as it streams, while a CPU-only DDR5 box drops to roughly 8 tokens per second and is better suited to batch work than live chat. The context window goes up to 256K, but treat that as a ceiling. Memory grows with what you actually fill, and at 128K of context the total footprint climbs to about 131 GB, so the long-context numbers assume a machine built for them.

Positioned against Devstral 2 123B, which sits at almost the same parameter count, Qwen 3.5 generally trades raw coding focus for breadth: it covers chat, reasoning, and vision in one model rather than specializing. That versatility is its standout trait, and the smaller Qwen 3 0.6B and 1.7B siblings remain the sensible choice when you only need lightweight chat on modest hardware. The license is Apache 2.0, so you can use it commercially and in production without restriction, which is rare at this capability level and a real reason to pick it over more encumbered weights.