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
Qwen2.5-72B-Instruct is the flagship of Alibaba's Qwen2.5 series, a 72-billion-parameter open-weight model released in September 2024 after training on 18 trillion tokens spanning code, mathematics, and multilingual text. It offers strong generalist performance across coding, instruction-following, and structured reasoning while remaining fully open-weight under Apache 2.0 — a combination that made it a widely referenced model in open-source evaluations and community benchmarking. The 128K context window and built-in structured output support made it a common choice for document analysis and multi-step agentic pipeline development.
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.
1 year newer
Qwen2.5 72B Instruct
Alibaba / Qwen
2024-09-19
Qwen3.5-397B-A17B
Alibaba / Qwen
2026-02-16
Available providers and their performance metrics
Qwen2.5 72B Instruct
Qwen3.5-397B-A17B
Qwen2.5 72B Instruct
Qwen3.5-397B-A17B