Qwen3.6-35B-A3B
Qwen3.6-35B-A3B is a mixture-of-experts text generation model from Qwen with a 262,144 token context window.
Qwen
DeepInfraMixture-of-experts text generation with long context
Qwen3.6-35B-A3B is a mixture-of-experts (MoE) language model developed by Qwen, released in July 2025. It has 35.6 billion total parameters but activates only 3.6 billion per forward pass, which reduces compute requirements while retaining a large parameter count. The model supports a context window of up to 262,144 tokens, making it suitable for tasks that require processing long documents or extended conversations.
The model is designed for text generation tasks including instruction following, reasoning, coding, and multilingual content. Its MoE architecture means it can handle a broad range of tasks without activating its full parameter set on every token, offering a balance between capacity and efficiency. It is served through DeepInfra on MindStudio and exposes sampling controls including Top P, Top K, Min P, presence penalty, repetition penalty, and frequency penalty.
What Qwen3.6-35B-A3B supports
Long Context Window
Supports up to 262,144 tokens of context, enabling processing of long documents, codebases, or extended multi-turn conversations in a single request.
Mixture-of-Experts Architecture
Uses a sparse MoE design with 35.6B total parameters but only 3.6B active per token, reducing per-token compute while maintaining broad model capacity.
Instruction Following
Trained to follow natural language instructions across a wide range of tasks including summarization, Q&A, and structured generation.
Code Generation
Capable of generating, explaining, and debugging code across multiple programming languages as part of its general text generation training.
Multilingual Text Generation
Supports text generation in multiple languages, consistent with the broader Qwen model family's multilingual training.
Sampling Parameter Control
Exposes six sampling controls — Top P, Top K, Min P, presence penalty, repetition penalty, and frequency penalty — for fine-grained output tuning.
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Get Started FreeCommon questions about Qwen3.6-35B-A3B
What is the context window size for Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B supports a context window of 262,144 tokens, and the maximum response size is also 262,144 tokens.
How does the mixture-of-experts architecture work in this model?
The model has 35.6 billion total parameters but activates only approximately 3.6 billion parameters per forward pass. This sparse activation reduces the compute cost per token compared to a dense model of equivalent total size.
What sampling parameters can I configure for this model?
You can configure Top P, Top K, Min P, presence penalty, repetition penalty, and frequency penalty to control the model's output distribution and reduce unwanted repetition.
What is the pricing for Qwen3.6-35B-A3B on MindStudio?
Pricing information is not published in the available metadata. You should check MindStudio's pricing page or your account dashboard for current usage costs.
What is the knowledge cutoff date for Qwen3.6-35B-A3B?
The specific training data cutoff date is not listed in the available metadata. The model was released in July 2025; consult Qwen's official documentation for the exact knowledge cutoff.
Does Qwen3.6-35B-A3B support image or video inputs?
No. Based on the available metadata, this model is a text-only model and does not support image or video inputs.
Parameters & options
Nucleus sampling. Considers only tokens whose cumulative probability exceeds this threshold.
Limits sampling to the K most likely tokens at each step. Set to 0 to disable.
Minimum probability threshold relative to the most likely token. Filters out unlikely tokens.
Penalizes tokens that have already appeared in the output, encouraging new topics.
Penalizes repeated tokens. Values above 1 discourage repetition; values below 1 encourage it.
Penalizes tokens based on how often they have already appeared, reducing verbatim repetition.
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