Qwen3.8 27B

Name: Qwen3.8 27B
Author: Alibaba

AlibabaOpen WeightsPending Human Review

Qwen3.8-27B is the dense open-weight tier of the Qwen3.8 release, with native vision support and a hybrid-attention language backbone. It targets coding, professional work, reasoning, and visual agents at a substantially smaller deployment footprint than the Max-scale checkpoint. Reasoning effort and preserved thinking support multi-turn agent workflows. Apache-2.0 weights allow self-hosting with a native 256K context and optional extension. Its multimodal capabilities and license are specific to this dense tier, differing from the text-only 2.4T open checkpoint.

2026-08-14

27B

Dense hybrid Gated DeltaNet/gated-attention Transformer with vision encoder

Apache-2.0

Compare with other models

Specifications

Parameters: 27B
Architecture: Dense hybrid Gated DeltaNet/gated-attention Transformer 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

Capabilities & Limitations

Capabilities: reasoningcode generationtool usevisual reasoningpreserved thinking
Known Limitations: Native context is 262,144 tokens; million-token operation requires extension.Lower reasoning effort can lead to extra agent retries rather than lower overall latency.
Notable Use Cases: coding assistantsresearch agentsdocument analysislocal visual agents
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

Alibaba

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

Alibaba

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.