"Qwen3.6-35B-A3B is a Mixture-of-Experts (MoE) model with: Total Parameters 35 Billion; Active Parameters ~3 Billion; Architecture Sparse MoE; Context Length 262K (up to 1M with YaRN); Modality Text + Image + Video; License Apache 2.0. The key idea: only a small portion of the model is used per request, making it much more efficient."
"Instead of activating all parameters: Activates only: Result: Sparse MoE = Massive Efficiency. The model uses a sparse Mixture-of-Experts design so only a subset of experts runs for each input, reducing compute while maintaining strong capability across tasks."
"This is where Qwen3.6 shines. It's not just a chatbot - it behaves like a developer assistant that understands entire codebases. Key Capabilities: Repository-level reasoning; Frontend generation; Terminal-based workflows; Multi-step coding tasks. The system is developer-focused for coding, reasoning, and multimodal tasks."
"One of the coolest features: Thinking Mode (Default) Model outputs reasoning inside <think> tags. Better for: Non-Thinking Mode. How to disable thinking: """
Qwen3.6-35B-A3B is a sparse Mixture-of-Experts model with 35B total parameters and about 3B active parameters per request. It supports a 262K context length, with up to 1M using YaRN, and handles text plus image and video inputs. The model is designed for agentic coding, including repository-level reasoning, frontend generation, terminal-based workflows, and multi-step coding tasks. Its sparse MoE architecture activates only a subset of parameters, improving efficiency. It uses a hybrid design combining DeltaNet and attention with MoE components, including gated DeltaNet for faster long-context processing and gated attention (GQA) to reduce memory usage. It also offers a thinking mode that outputs reasoning in <think> tags.
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