Comprehensive side-by-side LLM comparison
Qwen3.5-397B-A17B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Alibaba / Qwen
Qwen3 Coder Next is a coding-specialized open-weight model from Alibaba's Qwen3 family, built on the Qwen3-Next architecture with hybrid attention and Mixture-of-Experts design optimized for local development and agentic coding workflows. It targets on-device and self-hosted deployments requiring a capable coding agent that can operate within consumer hardware constraints.
Alibaba / Qwen
Qwen3.5-397B-A17B is a 397-billion-parameter mixture-of-experts model from Alibaba's Qwen team, released in February 2026 as the open-weight flagship of the Qwen3.5 series, featuring 17 billion active parameters per forward pass through a hybrid linear-attention and sparse-MoE architecture based on Gated Delta Networks. The model was co-trained on text, images, and video using early fusion, making it natively multimodal across a 262K token context window, while achieving significantly higher inference throughput than comparable dense models due to its sparse computation design. At release it was one of the most capable open-weight models publicly available, offered under Apache 2.0 and accessible through Alibaba's DashScope API as the Qwen3.5-Plus endpoint.
12 days newer
Qwen3 Coder Next
Alibaba / Qwen
2026-02-04
Qwen3.5-397B-A17B
Alibaba / Qwen
2026-02-16
Available providers and their performance metrics
Qwen3 Coder Next
Qwen3.5-397B-A17B
Qwen3 Coder Next
Qwen3.5-397B-A17B