Comprehensive side-by-side LLM comparison
Qwen3.5-397B-A17B leads with 2.0% higher average benchmark score. Qwen3.5-397B-A17B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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.
StepFun
Step-3.5-Flash, released by StepFun on February 2, 2026, is a Mixture-of-Experts large language model with 197 billion total parameters and approximately 11 billion active parameters per inference. It features a 256K token context window using a 3:1 sliding-window-to-full-attention ratio, processing 100–350 tokens per second. Step-3.5-Flash targets agentic tasks, coding workflows, and open-source deployments requiring frontier reasoning capabilities with efficient inference, under an Apache 2.0 license.
14 days newer
Step-3.5-Flash
StepFun
2026-02-02
Qwen3.5-397B-A17B
Alibaba / Qwen
2026-02-16
Average performance across 1 common benchmarks
Qwen3.5-397B-A17B
Step-3.5-Flash
Performance comparison across key benchmark categories
Qwen3.5-397B-A17B
Step-3.5-Flash
Available providers and their performance metrics
Qwen3.5-397B-A17B
Step-3.5-Flash
Qwen3.5-397B-A17B
Step-3.5-Flash