Comprehensive side-by-side LLM comparison
Qwen3.5-397B-A17B leads with 3.3% higher average benchmark score. Qwen3.5-397B-A17B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
DeepSeek
DeepSeek-V3.2-Exp (DeepSeek-V3.2 Thinking), released by DeepSeek in September 2025, is the experimental preview release of the DeepSeek-V3.2 model featuring 685 billion total parameters and integrated thinking capabilities. It introduced the architecture and training approaches that became the foundation of the final V3.2 release, including thinking in tool-use and hybrid reasoning modes.
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.
4 months newer

DeepSeek-V3.2 Thinking
DeepSeek
2025-09-29
Qwen3.5-397B-A17B
Alibaba / Qwen
2026-02-16
Context window and performance specifications
Average performance across 1 common benchmarks
DeepSeek-V3.2 Thinking
Qwen3.5-397B-A17B
Performance comparison across key benchmark categories
DeepSeek-V3.2 Thinking
Qwen3.5-397B-A17B
Available providers and their performance metrics
DeepSeek-V3.2 Thinking
DeepSeek
Qwen3.5-397B-A17B
DeepSeek-V3.2 Thinking
Qwen3.5-397B-A17B
DeepSeek-V3.2 Thinking
Qwen3.5-397B-A17B