Qwen3.8 27B

Qwen

Built on the architectural foundation of Qwen3.5, Qwen3.8 delivers substantial gains across coding, professional work, research, and long-horizon agentic tasks. Qwen3.8-27B brings these advances to a compact, deployment-friendly dense model: a native vision-language model that understands images and videos, with flexible thinking control, designed to carry complex, multi-step tasks through to completion with greater reliability.

Specs

Model

Family
Qwen
Variant
3.8 27B
Parameters
27B dense
Weights
Open
License
Apache-2.0

Limits

Context
262,144 tokens
Max output
131,072 tokens

Modalities

Input
Text Image Video
Output
Text

Capabilities

Reasoning
Yes
Reasoning control
On / off, Effort levels
Tool calling
Yes

Dates

Released
14 Aug 2026

DFlash 2: Keep Drafting Parallel

DFlash 2 is the successor to our widely deployed parallel drafter: close to 3× the speed of autoregressive decoding, with the same output. Drafters for Qwen3.8-27B and Meta's Muse Glimmer are out today.

Inco AI
inco.ai

Qwen 3.8 27B is excellent, but it defaults to wildly overthinking things

Friday’s big release was Qwen 3.8 27B, an Apache 2 licensed 27B parameter vision-capable LLM from Alibaba’s Qwen research lab. I’ve been looking forward to this one: 27B is an …

Simon Willison
simonwillison.net

Qwen 27B 3.8: Non-Thinking vs XHigh Thinking

Qwen 27B 3.8 was given the same CRUDbench task in non-thinking mode and XHigh thinking mode.

x.com

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An open-weights multimodal MoE model that doubles as an early preview of the Qwen4 architecture, the same role Qwen3-Next played for Qwen3.5. It pairs Gated DeltaNet with Qwen Sparse Attention, widens the residual stream into four gated branches, and adds 51B N-gram embedding parameters that cost almost nothing per token. Natively 262K context, extensible to 1M with YaRN.

Qwen Community License 1.05w ago

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