Can I run Qwen 3.5 27B?

Qwen 3.5 27B is the model you reach for when an 8B feels too thin and you have real hardware to spend. It is a dense 27B that handles chat, reasoning, coding, and vision, so it doubles as a local workhorse rather than a single-trick assistant. The footprint is the catch: at 4-bit it lands around 16.4 GB, and you want at least 24 GB of RAM to load it cleanly. That rules out a 12 GB card like an RTX 3060, where it simply does not fit, and points you at a 24 GB GPU or an Apple Silicon Mac with generous unified memory.

On an RTX 4090 you can expect around 52 tokens per second at 4-bit, which streams faster than you read and stays comfortable for interactive work. On an M-series Max it settles near 21 tokens per second, still fine for chat and coding but slower on long generations; pure CPU on DDR5 drops to roughly 3 tokens per second, which is patience territory. The 256K context is the headline number, but treat it as a ceiling: at 128K the total memory climbs to about 45.4 GB, so on a 24 GB card keep working context well below the maximum.

The natural comparison is Gemma 3 27B, the other open-weight 27B with vision in this size class. Gemma tends to be the safer pick if you are mainly after polished chat and image understanding, while Qwen 3.5 27B generally leans stronger on coding and structured reasoning, which is where its standout value sits for developers. The big practical win is licensing: it ships under Apache 2.0, so you can use it commercially and in production with no provider-specific strings attached, unlike the open-weight terms that come with Gemma.