Alibaba (Qwen) · 2026-08-14 · major
Qwen3.8-27B — a 27B open model that beats Opus 4.6 Max on SWE-bench Pro
Qwen3.8-27B is Alibaba's new 27B dense open-weights model with built-in vision, released under Apache-2.0. It scores 61.7 on SWE-bench Pro and 84.3 on OSWorld-Verified, ahead of Opus 4.6 Max on both.
A 27B dense model with open Apache-2.0 weights that reads images and video and runs long agentic coding jobs.
Quick facts
| Maker | Alibaba (Qwen) |
|---|---|
| Size | 27B dense, 64 layers |
| Context window | 262,144 native, up to 1,000,000 |
| License | Apache-2.0 |
| Modality | Text, image and video in |
| Formats | BF16 and FP8 checkpoints |
| Thinking | On by default, tunable low / medium / xhigh |
Benchmarks
| Qwen3.8-27B | 61.7% | |
|---|---|---|
| Qwen3.7-Plus | 57.6% | |
| Qwen3.6-27B | 53.5% | |
| Opus 4.6 Max | 53.4% | |
| Muse Glimmer-30B | 51.2% |
| Qwen3.8-27B | 84.3% | |
|---|---|---|
| Qwen3.7-Plus | 73.3% | |
| Opus 4.6 Max | 72.7% | |
| Muse Glimmer-30B | 65.9% | |
| Qwen3.6-27B | 63.9% |
| Opus 4.6 Max | 78.2% | |
|---|---|---|
| Qwen3.8-27B | 73% | |
| Qwen3.7-Plus | 64% | |
| Qwen3.6-27B | 63.4% | |
| Muse Glimmer-30B | 51.7% |
What is it?
Qwen3.8-27B adds native vision to Alibaba's compact dense line: it takes images and hour-scale video alongside text, and thinking mode is on by default with a per-request off switch. The weights are on Hugging Face under Apache-2.0, in both BF16 and FP8. The context window is 262,144 tokens natively and stretches to 1,000,000.
How does it work?
Under the hood sit 64 layers that repeat one hybrid block 16 times: three Gated DeltaNet linear-attention layers for every single full Gated Attention layer. Qwen3.8-27B was trained with multi-token prediction, and a `reasoning_effort` setting picks low, medium or xhigh reasoning depth per call. Thinking from earlier turns is kept by default so agents do not lose their train of thought.
Why does it matter?
Strong agentic coding now comes in weights you can host yourself. On SWE-bench Pro the 27B model scores 61.7 against 53.4 for Opus 4.6 Max, and computer use on OSWorld-Verified climbs from Qwen3.6-27B's 63.9 to 84.3. Teams that could not send code to a closed API get a model that competes on the same tasks.
Who is it for?
developers running local or self-hosted models
Frequently asked questions
- Is Qwen3.8-27B free for commercial use?
- Qwen3.8-27B ships under the Apache-2.0 licence, which allows commercial use, modification and redistribution without a separate agreement with Alibaba. That is looser than Qwen3.8-Max, the 2.4T flagship, which uses Qwen's own bespoke licence. Both the BF16 and the FP8 checkpoints on Hugging Face carry the same Apache-2.0 terms.
- How much better is Qwen3.8-27B than Qwen3.6-27B?
- Qwen3.8-27B improves on Qwen3.6-27B on every benchmark Qwen published. Agentic terminal coding on Terminal Bench 2.1 rises from 63.4 to 73.0, SWE-bench Pro from 53.5 to 61.7, and computer use on OSWorld-Verified from 63.9 to 84.3. The biggest jump is DeepSWE 1.1, which goes from 13.3 to 42.2.
- Can I get Qwen3.8-27B as a hosted API?
- A hosted Qwen3.8-27B is planned but not live yet. The model card points to Qwen Cloud for managed inference and says the 27B service will offer a 1M-token context by default plus built-in tools, but marks it as coming soon with no date given. For now the open weights are the way to run it.
- Which serving frameworks support Qwen3.8-27B?
- Qwen publishes ready-made recipes for Qwen3.8-27B on SGLang, vLLM and TokenSpeed, and the Hugging Face repository holds the post-trained weights in Transformers format. Qwen recommends those dedicated serving engines over plain Transformers for production or high-throughput work, and warns that throughput varies a lot between frameworks.
- Does Qwen3.8-27B beat closed frontier models?
- Qwen3.8-27B leads Opus 4.6 Max on several agentic benchmarks in Qwen's own table: 61.7 versus 53.4 on SWE-bench Pro, 84.3 versus 72.7 on OSWorld-Verified, and 90.3 versus 88.8 on LiveCodeBench v6. Opus 4.6 Max still wins Terminal Bench 2.1 at 78.2 to 73.0, plus GPQA Diamond and HLE.
Try it
Model id: Qwen/Qwen3.8-27B (BF16) or Qwen/Qwen3.8-27B-FP8