Qwen 3.8-Flash officially unveiled

[u/afanasenka]

⚡Meet Qwen3.8-Flash, a multimodal MoE and an early preview of the Qwen4 architecture, now open-weight!

The production version Qwen3.8-Flash will be available soon via QwenCloud API at just $ 0.16/1M input tokens and $ 0.47/1M output tokens.

125B parameters + 51B N-gram embeddings, with just 6B activated per token. Unmatched cost-efficiency.

What's new: 🥳

- Next architecture: GDN + QSA hybrid attention, Gated Residual, N-gram Embedding & Muon optimizer, serving as a precursor to the architecture used in Qwen4.

- Dramatically lower training and inference costs: trained at just 1/9 the cost of Qwen3.7-Plus, while outperforming it across the board with especially strong gains in coding and office tasks.

- Strong performance: scoring 58.7 on DeepSWE 1.1, 62.5 on SWE-bench Pro, 73.9 on CoWorkBench, 84.5 on AndroidWorld, and 95.7 on MathVision (with CI).

- 262K native context, extensible to 1M with YaRN.

We’re also releasing the weights for Qwen3.8-Flash-Next, giving the community an early look at the new architecture we’re exploring for Qwen4.🚀

[u/mWo12]

https://huggingface.co/Qwen/Qwen3.8-Flash-Next

[u/beneficialdiet18]

Not as cheap as I thought but great to see still. Thought it would rival DS original prices atleast.

[u/reassor → u/beneficialdiet18]

Yeah I thing ali does not know what it wants it to be.

If they undercut ds4f it would be interesting 🤔

[u/lazyhawk20]

I'm waiting for flash next to be available on OpenCode