Qwen3.6

Name: Qwen3.6
Author: Alibaba

AlibabaOpen WeightsPending Human Review

Qwen3.6 is an open-weight multimodal update focused on practical agentic coding and development stability. The first checkpoint is a 35B-A3B MoE model, followed on April 22 by a 27B dense model. Both build on the Qwen3.5 hybrid-attention architecture and support preserving reasoning history across turns. Images and video enable visually grounded coding and reasoning. Apache-2.0 weights support local deployment with a native 256K context; larger contexts require explicit extension. The proprietary hosted Plus and Flash tiers are distinct service identities.

2026-04-16

35B total / 3B active MoE; 27B dense

Hybrid Gated DeltaNet/gated-attention Transformer; MoE and dense variants with vision encoder

Apache-2.0

Compare with other models

Specifications

Parameters: 35B total / 3B active MoE; 27B dense
Architecture: Hybrid Gated DeltaNet/gated-attention Transformer; MoE and dense variants with vision encoder
License: Apache-2.0
Context Window: 262,144 tokens
Type: multimodal
Modalities: textimagevideo

Benchmark Scores

Advanced Specifications

Model Family: Qwen
API Access: Not Available
Chat Interface: Not Available
Variants: Qwen3.6-35B-A3B (2026-04-16)Qwen3.6-27B (2026-04-22)

Capabilities & Limitations

Capabilities: reasoningcode generationtool usevisual reasoningpreserved thinkingagentic coding
Known Limitations: Self-hosting requires sufficient memory for all model weights, including inactive experts.Reasoning and agent benchmark results depend on the harness and sampling settings.Preserved thinking requires correct multi-turn message handling.The native context differs from the hosted Plus and Flash services.
Notable Use Cases: coding assistantsresearch agentsdocument analysisvisual interface development
Function Calling Support: Yes
Tool Use Support: Yes

Resources

Related Models

IndustryLLM

Alibaba

IndustryLLM is Alibaba’s open-weight language model for industrial procurement and engineering-standard reasoning. It adapts Qwen3.5-35B-A3B-Base through continued pre-training on industrial documents and transactions followed by task-focused supervised fine-tuning. The 35.95B-parameter hybrid mixture-of-experts network activates approximately 3B per token. Training targets informal buyer language, ambiguous product codes, contradictory specifications, and evidence-based constraint evaluation. Apache-licensed BF16 weights are published. Its 262K architectural context is distinct from 12,288-token packed fine-tuning sequences; this record uses the supported training length conservatively. The September 25 paper predates later discovery-index coverage.

Typetext

Parameters35.95B total, approximately 3B active

2026-09-25

Open Weights

Details Compare

Qwen-Audio-3.1-Realtime

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Qwen-Audio-3.1-Realtime is a proprietary language-capable speech conversation model for fluid real-time dialogue. It combines speech reasoning with duplex interaction, allowing conversational responses rather than only transcription or speech synthesis. The 3.1 Plus update supports a 262,144-token context, function calling, web search, voice cloning, and additional system voices, while retaining the 3.0 Plus integration protocol. Hosted streaming APIs provide access; no downloadable weights or checkpoint parameter count is verified.

Qwen3.8-Omni-Flash

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Qwen3.8-Omni-Flash is a native omnimodal agent model built on the Qwen3.8-Flash-Next architecture. It accepts text, images, audio, and video in a million-token context, extending coding, GUI operation, and knowledge work to audio-visual productivity. Standard APIs return text, while the subsequently available Realtime variant supports text and speech output, multichannel audio, video aggregation, and remote MCP tools. Hosted access and companion plugins support video editing, multimedia summarization, and real-time conversations; its weights are not publicly released.