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qwopus3.8-27b-flash
# Qwen3.8-27B
> [!Note]
> This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format.
>
> These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, TokenSpeed, etc.
> [!Tip]
> For users seeking managed, scalable inference without infrastructure maintenance, the official Qwen API service is provided by Qwen Cloud.
> In particular, **Qwen3.8-27B** will be available as a hosted version with more production features, e.g., 1M context length by default, official built-in tools. For more information, please refer to the Qwen3.8-27B Overview. The service is coming soon. Stay tuned for updates.
Following the widespread community adoption of the Qwen3.5 and Qwen3.6 series, we are pleased to introduce Qwen3.8, the most capable generation in the Qwen open-model family to date.
...
Repository: localaiLicense: apache-2.0
qwen3.8-27b-uncensored-hauhaucs-aggressive-mtp
# Qwen3.8-27B
> [!Note]
> This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format.
>
> These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, TokenSpeed, etc.
> [!Tip]
> For users seeking managed, scalable inference without infrastructure maintenance, the official Qwen API service is provided by Qwen Cloud.
> In particular, **Qwen3.8-27B** will be available as a hosted version with more production features, e.g., 1M context length by default, official built-in tools. For more information, please refer to the Qwen3.8-27B Overview. The service is coming soon. Stay tuned for updates.
Following the widespread community adoption of the Qwen3.5 and Qwen3.6 series, we are pleased to introduce Qwen3.8, the most capable generation in the Qwen open-model family to date.
...
Repository: localaiLicense: apache-2.0
apodex-1.1-mini-q4
Apodex-1.1-mini is an Apache-2.0 Qwen3.5 mixture-of-experts model for
long-horizon research, data analysis, coding, file work, and tool use. It
activates about 3B of its 35.95B parameters per token and supports text and
image input with a context window of 262K tokens.
This default entry uses the recommended Q4_K_M GGUF and F16 vision
projector. An MTP-enabled build and a higher-quality Q8_0 model are
available as variants.
Repository: localaiLicense: apache-2.0
apodex-1.1-mini-q4-mtp
Apodex-1.1-mini with MTP speculative decoding enabled on the recommended
Q4_K_M GGUF. The model carries its native MTP head, so it needs no separate
draft model. The F16 vision projector supports multimodal prompts.
Repository: localaiLicense: apache-2.0
apodex-1.1-mini-q8
Apodex-1.1-mini in the higher-quality Q8_0 GGUF format, with the shared F16
vision projector for multimodal prompts.
Repository: localaiLicense: apache-2.0
glm-5.3-flash-q4
GLM-5.3-Flash is Z.ai's natively multimodal 320B-parameter mixture-of-experts
model with 18B active parameters. It combines sparse and linear attention
for coding, agentic work, tool use, vision, and long-context tasks. This
entry uses the UD-Q4_K_XL GGUF quantization and enables the model's MTP
speculative-decoding head.
Repository: localaiLicense: mit
glm-5.3-flash-q8
GLM-5.3-Flash is Z.ai's natively multimodal 320B-parameter mixture-of-experts
model with 18B active parameters. It combines sparse and linear attention
for coding, agentic work, tool use, vision, and long-context tasks. This
entry uses the higher-quality Q8_0 GGUF quantization and enables the model's
MTP speculative-decoding head.
Repository: localaiLicense: mit
qwen3.8-flash-next-q4
Qwen3.8-Flash-Next is Qwen's 125B-parameter, 6B-active experimental
vision-language mixture-of-experts model. It targets agentic coding,
reasoning, tool use, and long-context workloads with a native 262K-token
context window.
This default entry uses Unsloth's UD-Q4_K_XL GGUF and BF16 vision
projector. The linked variant uses the higher-quality Q8_0 quantization.
Repository: localaiLicense: other
qwen3.8-flash-next-q8
Qwen3.8-Flash-Next in the higher-quality Q8_0 GGUF format, with the shared
BF16 vision projector. This build preserves more model quality but needs
more memory than the default Q4 variant.
Repository: localaiLicense: other
dirk-qwen3.8-27b-q4
Dirk is a Qwen3.8 27B vision-language model with a concise chat template
for agentic coding, reasoning, tool use, and general knowledge tasks. It
preserves the model's MTP head for speculative decoding and supports a
262K-token context window.
This default entry uses the Q4_K_XL GGUF and F16 vision projector. A
higher-quality Q8_K_XL build is available as a variant.
Repository: localaiLicense: apache-2.0
dirk-qwen3.8-27b-q8
Dirk in the higher-quality Q8_K_XL GGUF format, with MTP speculative
decoding and the shared F16 vision projector for multimodal prompts.
Repository: localaiLicense: apache-2.0
ornith-1.0-9b-q4
Ornith-1.0-9B is an MIT-licensed Qwen3.5 model from Ornith AI for
agentic coding, reasoning, repository-level software tasks, and tool use.
It supports text and image input with a context window of 262K tokens.
This default entry uses the Q4_K_M GGUF and F16 vision projector. A
higher-quality Q8_0 model is available as a variant.
Repository: localaiLicense: mit
ornith-1.0-9b-q8
Ornith-1.0-9B in the higher-quality Q8_0 GGUF format, with the shared F16
vision projector for multimodal prompts.
Repository: localaiLicense: mit
ornith-1.5-9b-q4
Ornith-1.5-9B is an MIT-licensed Qwen3.5 model from Ornith AI for
agentic coding, reasoning, repository-level software tasks, and tool use.
It supports text and image input with a context window of 262K tokens.
This default entry uses the Q4_K_M GGUF and BF16 vision projector. A
higher-quality Q8_0 model is available as a variant.
Repository: localaiLicense: mit
ornith-1.5-9b-q8
Ornith-1.5-9B in the higher-quality Q8_0 GGUF format, with the shared BF16
vision projector for multimodal prompts.
Repository: localaiLicense: mit
ornith-1.5-9b-obliterated-q4
Ornith-1.5-9B OBLITERATED is a refusal-removed derivative for alignment
research, red teaming, coding, reasoning, and agentic tasks. Its safety
guardrails are removed, and the publisher reports some capability loss
compared with the original model.
This default entry uses the Q4_K_M GGUF and BF16 vision projector. The
linked variant uses the higher-quality Q8_0 quantization.
Repository: localaiLicense: mit
ornith-1.5-9b-obliterated-q8
Ornith-1.5-9B OBLITERATED in the higher-quality Q8_0 GGUF format, with the
shared BF16 vision projector. Its safety guardrails are removed, and the
publisher recommends this quantization for better behavior fidelity.
Repository: localaiLicense: mit
ornith-1.5-35b-a3b-q4
Ornith-1.5-35B-A3B is an MIT-licensed Qwen3.5 mixture-of-experts model
from Ornith AI for agentic coding, reasoning, repository-level software
tasks, and tool use. It activates about 3B parameters per token and
supports text and image input with a context window of 262K tokens.
This default entry uses the Q4_K_M GGUF and BF16 vision projector. A
higher-quality Q8_0 model is available as a variant.
Repository: localaiLicense: mit
ornith-1.5-35b-a3b-q8
Ornith-1.5-35B-A3B in the higher-quality Q8_0 GGUF format, with the shared
BF16 vision projector for multimodal prompts.
Repository: localaiLicense: mit
thomson-1.0-small-q4
Thomson-1.0-Small is a 35B-parameter mixture-of-experts model with about
3B active parameters. It focuses on legal, tax, journalism, research,
reasoning, tool use, and document processing. It supports text and image
input with a native context window of 262K tokens.
This default entry uses the Q4_K_M GGUF and BF16 vision projector. A
higher-quality Q8_0 model is available as a variant.
Repository: localaiLicense: polyform-strict-1.0.0
thomson-1.0-small-q8
Thomson-1.0-Small in the higher-quality Q8_0 GGUF format, with the shared
BF16 vision projector for multimodal prompts.
Repository: localaiLicense: polyform-strict-1.0.0
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