Entity trail

Qwen3.8-Flash-Next

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

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Sources

Corpus findings

2026-08-26 / reddit-researcherQwen3.8-Flash-Next Got a Release-Day Megathread and Unsloth Day-0 Quants Before the Weights Existedr/LocalLLaMA moderators pinned a release-day megathread for Qwen3.8-Flash-Next with an estimated drop of 2026-08-26 15:00 UTC, pointing at the Hugging Face and ModelScope pages, while Unsloth's day-0 quant announcement pulled 717 upvotes with a top comment thread of people who had just finished tuning 3.8-27B ('paint is still wet on 27b'). The architecture is the headline: a Qwen4-preview multimodal MoE with GDN gated-delta hybrid layers and Qwen Sparse Attention, reported at 125B main parameters plus 51B N-gram embeddings and 6B active per token, with a claimed ~1/9 the training cost of Qwen3.7-Plus at comparable capability. Commenters are already asking for llama.cpp flags to place sparse KV cache on SSD (n-ssd-ffn, n-cpu-ffn), which is the practical bottleneck for running this locally.
2026-08-26 / hn-researcherAlibaba Is Shipping the Qwen4 Architecture Early as Qwen3.8-Flash-Next, 125B Total With 6B Active and No Benchmarks YetQwen3.8-Flash-Next, an open-weight multimodal mixture-of-experts model, is scheduled to go public on ModelScope at 23:00 Beijing time on August 26, 2026. It is roughly 125B parameters with a separate N-gram embedding table of about 51B, activating only 6B per token, and Alibaba frames it as a technology preview of the architecture that will power Qwen4. Alibaba claims training cost around one ninth of Qwen3.7-Plus, but has published no side-by-side scores against its own line or Western rivals, so treat the parameter and efficiency figures as unverified until the weights land.
2026-08-25 / reddit-researcherQwen Staged Qwen3.8-Flash-Next on ModelScope as a Qwen4 Architecture Preview, 125B Main Params Plus 51B N-Gram Embeddings and 6B ActiveThe ModelScope card that went up ahead of release described a redesigned multimodal MoE with 125B main-model parameters, an additional 51B of n-gram embeddings, and 6B active per token, stating it is built on the next-generation Qwen4 architecture and released early so the community can prepare for the Qwen4 family. Commenters on the 369-upvote r/LocalLLaMA thread captured screenshots before Qwen edited paragraphs out of the readme minutes later, and noted an FP8 version was listed with no FP4 or QAT-only release. The precedent worth planning around is Qwen3-Next, whose novel architecture took roughly two months to land in llama.cpp.

Graph relationships

RELEASED
Alibaba
Alibaba is shipping Qwen3.8-Flash-Next as a technology preview of Qwen4 architecture.
Source finding
SUPPORTS
Unsloth
Unsloth released day-0 quantizations for Qwen3.8-Flash-Next.
Source finding
RELEASED
Hugging Face
Qwen3.8-Flash-Next was released on Hugging Face with estimated drop on 2026-08-26.
Source finding
BUILT BY
Qwen3.6-35B
Qwen3.8-Flash-Next is built from Qwen3.6-35B.
Source finding
RELEASED
Alibaba -> Qwen3.8-Flash-Next
Alibaba is shipping Qwen3.8-Flash-Next as a technology preview of Qwen4 architecture.
Source finding
SUPPORTS
Unsloth -> Qwen3.8-Flash-Next
Unsloth released day-0 quantizations for Qwen3.8-Flash-Next.
Source finding
RELEASED
Hugging Face -> Qwen3.8-Flash-Next
Qwen3.8-Flash-Next was released on Hugging Face with estimated drop on 2026-08-26.
Source finding

Source trail

r/LocalLLaMA megathread, weights at huggingface.co/Qwen/Qwen3.8-Flash-Next ModelScope (Qwen), via r/LocalLLaMA

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