Comprehensive side-by-side LLM comparison
Qwen3.5-397B-A17B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
DeepSeek
DeepSeek-R1, released by DeepSeek on January 20, 2025, is a large reasoning model with 671 billion total parameters (37 billion active in its MoE architecture) designed for extended chain-of-thought reasoning. It features a 128K token context window and demonstrated strong performance on mathematics, coding, and scientific reasoning benchmarks at its release. DeepSeek-R1 targets complex analytical tasks, competitive programming, and applications requiring deep deliberative reasoning under an open MIT license.
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

DeepSeek-R1
DeepSeek
2025-01-20
Qwen3.5-397B-A17B
Alibaba / Qwen
2026-02-16
Context window and performance specifications
Available providers and their performance metrics
DeepSeek-R1
DeepSeek
Qwen3.5-397B-A17B
DeepSeek-R1
Qwen3.5-397B-A17B
DeepSeek-R1
Qwen3.5-397B-A17B