Qwen
Qwen3.8-27B
Apache 2.0 Qwen3.8 dense VLM for local and self-hosted work — native 262K context, image and video input, thinking on by default but can be turned off. Distinct from hosted Qwen3.8-Max.
Catalog record checked August 14, 2026; individual provider fields may change.
| Specification | Qwen3.8-27B |
|---|---|
| Provider | Qwen |
| Tier | Balanced |
| Context window | 262K |
| Max output | 131K |
| Input / 1M tokens | Not verified |
| Output / 1M tokens | Not verified |
| Weights | Open |
| Parameters | 27B dense |
| Modalities | text, image, video |
| Released | August 14, 2026 |
Best for
- Local multimodal agents
- Self-hosting a dense 27B VLM
- Apache 2.0 deployments
Watch out
Common questions
Qwen3.8-27B
Answered from the verified figures on this page rather than general guidance.
What is Qwen3.8-27B's context window?
Qwen3.8-27B accepts about 262K tokens of context. That only matters if you routinely send very long documents, large codebases, or multi-turn histories that approach that limit.
What is Qwen3.8-27B best for?
Qwen3.8-27B is a balanced tier from Qwen. It suits local multimodal agents, self-hosting a dense 27b vlm, apache 2.0 deployments. The Hugging Face repo was created 2026-08-05; this row uses the 2026-08-14 card revision. Hosted 1M-context API is documented as coming soon. Vendor SWE-bench Pro 61.7 and DeepSWE 42.2 used a Claude Code harness, not swebench.com or the public Datacurve DeepSWE board. YaRN can extend context toward 1M.
Can I self-host Qwen3.8-27B?
Qwen3.8-27B publishes open weights, but self-hosting depends on the licence, hardware footprint, quantisation quality, and serving stack. A hosted API is often cheaper until you have measured throughput and concurrency on your own hardware.
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Head-to-head model comparisons
These are the published pairings that put this model against a plausible alternative.