Qwen3.5 27B

Qwen3.5 27B belongs to an open-source multimodal family that the Ollama library describes as delivering strong utility and performance across a wide size range, with 27B sitting in the mid-tier alongside 0.8B, 2B, 4B, 9B, 35B, and 122B siblings. The Ollama page header tags indicate the variant exposes a thinking/reasoning toggle alongside vision and tool-calling capability, aligning it with practical agentic and assistant workloads rather than narrow single-task use. Its distribution includes both MLX and llama.cpp builds, which broadens the practical paths for running it on consumer and workstation hardware.

The embedded vision configuration in the qwen3.5:27b Ollama asset defines an extremely large longest edge of 16,777,216 pixels, suggesting the visual encoder is designed to accept high-resolution image inputs without aggressive downsampling, which is useful for document, chart, and screenshot understanding. The model is also the subject of active community optimization on NVIDIA DGX Spark / GB10 hardware, where an NVIDIA developer-forums thread reports single-GPU llama.cpp throughput above 30 tokens per second at tensor-parallel size 1, showing it can be run interactively on compact local accelerators. These characteristics make 27B a balanced mid-size option for users who want multimodal understanding plus reasoning without committing to the larger 35B or 122B variants.