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Model Detail

JonathanColetti logo

Qwen3.8-27B-Uncensored-GGUF

▲ 10.6%
Provider: JonathanColettiCategory: llmPipeline: text-generationParameters: 27B
DB Score
2.2
Downloads
2.4M
Likes
960
Day
+10.6%
Week
+0.0%
Month
+0.0%
Overview

Qwen3.8-27B-Uncensored-GGUF is a large language model with 27B parameters released by JonathanColetti. The model is registered under the text-generation pipeline tag on Hugging Face, distributed under the permissive apache-2.0 license.

Technical

Qwen3.8-27B-Uncensored-GGUF ships with 27B parameters, distributed as a quantized weight variant for lower-VRAM inference. The apache-2.0 license is permissive, allowing commercial deployment and derivative work without per-seat fees, though attribution requirements still apply.

Trending Signal

Downloads of Qwen3.8-27B-Uncensored-GGUF have moved +10.6% over the past 24 hours. That is a slight downtrend, consistent with normal cooling as newer models compete for the same workloads. These numbers are signal, not guarantee — week-over-week download counts on Hugging Face also reflect mirror traffic, CI scrapes, and one-off benchmarking runs.

Read about databubble_score →
Use Cases

Qwen3.8-27B-Uncensored-GGUF is best fit for general-purpose chat and instruction-following workloads. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.

Download History
Model Info
Licenseapache-2.0
Recent newsView all news →
Related News
arxiv4d ago

On the Design of Qwen3.8-Next Architecture: Evaluation, Efficiency, and Training Stability

arXiv:2608.30320v1 Announce Type: new Abstract: We describe the architecture and ablations of Qwen3.8-Flash-Next, a sparse mixture-of-experts model with 125B parameters, 6B activated per token, and additional 51B parameters of n-gram embedding tables held off the accelerator. On fourteen pre-trainin

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