# Qwen3.8-27B Drops Apache Multimodal Weights — the Workstation Companion to Max

Times of AI Desk · 2026-08-14 · Models

[https://timesof.ai/2026/08/alibaba-qwen-3-8-27b-open-weights](https://timesof.ai/2026/08/alibaba-qwen-3-8-27b-open-weights)

> Alibaba’s Qwen team posted Qwen3.8-27B on Hugging Face — a 27-billion-parameter native vision-language dense model with 262K context (extensible to 1M), thinking mode by default, and Apache 2.0 weights — the local companion to July’s 2.4T Qwen3.8-Max preview. Vendor SWE-bench Pro 61.7 is lab-run.

**Corrected October 14, 2026:** Marked SWE-bench Pro and OSWorld figures as vendor-run with harness differences, removed an unsupported characterization of the Max preview, and turned an internal reference into a link.

The 2.4T Max preview was a datacenter artifact. **27B Apache multimodal** is what actually runs on a workstation next to **Muse Glimmer 30B** (Aug 10). Its SWE-Pro / OSWorld numbers are vendor-run, with harness settings that differ from rivals’.

**Alibaba’s Qwen team** released **Qwen3.8-27B** weights at **[Qwen/Qwen3.8-27B](https://huggingface.co/Qwen/Qwen3.8-27B)**. The checkpoint is a **27B** **dense** **native vision-language** model (images and video), **Apache 2.0**, **262,144** native context (YaRN to **1,000,000**). Thinking mode is **on by default**, with `reasoning_effort` at **xhigh / medium / low**. It follows **Qwen3.8-Max-Preview** (2.4T), previewed **July 19**.

## What the model card says

| Item | Official card |
|------|----------------|
| **Type** | Causal LM + vision encoder; 64 layers; hybrid Gated DeltaNet + Gated Attention |
| **Params** | **27B** (card); HF filesize line also says **28B** params in BF16 |
| **Context** | **262,144** native; **1M** via YaRN |
| **License** | **Apache 2.0** |
| **Vendor SWE-bench Pro** | **61.7** (Claude Code harness; Qwen notes Opus 4.6 Max official **53.4** on their re-eval table) |
| **Vendor DeepSWE 1.1** | **42.2** |
| **Vendor OSWorld-Verified** | **84.3** |
| **Hosted** | Qwen Cloud version “coming soon,” 1M context + built-in tools |

Qwen’s table is **lab-run**. Several rows use in-house benches (QwenSWEBench, CoWorkBench, RecreationBench). Treat **61.7 SWE-bench Pro** as **vendor-claimed** until independent boards replicate.

## Independent rankings

| Source | Snapshot | Standing |
|--------|----------|----------|
| **Hugging Face card / ScaleAI SWE-bench Pro eval widget** | Launch card | Displays **61.7** (same as vendor table; asterisked) |
| **Artificial Analysis / LMArena** | Research window Aug 17 | **No dated Index or Elo** cited here for 3.8-27B — **not yet independently ranked** in those boards at write time |

## Limits

- Vendor benches are lab-run; several use in-house harnesses.
- No Artificial Analysis Index or LMArena Elo at write time.
- Whether Max weights follow or stay API-only is open.

## Sources

- [Hugging Face: Qwen/Qwen3.8-27B (Apache 2.0)](https://huggingface.co/Qwen/Qwen3.8-27B)
- [Qwen blog citation on the card: qwen.ai/blog?id=qwen3.8](https://qwen.ai/blog?id=qwen3.8)
- Times of AI: [Qwen3.8-Max preview](https://timesof.ai/2026/07/alibaba-qwen-3-8-max-preview) (July 19, 2026) — Max preview, not this weight drop
- [MarkTechPost: Alibaba Previews Qwen3.8-Max, a 2.4 Trillion-Parameter Multimodal Model (July 19, 2026)](https://www.marktechpost.com/2026/07/19/alibaba-previews-qwen3-8-max-a-2-4-trillion-parameter-multimodal-model-days-after-moonshots-kimi-k3-open-weight-launch/)