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Open-weight model · Image and text to text

Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-MXFP4

by Solstice-AI Solstice-AI/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-MXFP4

Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-MXFP4 is an open-weight model for image and text to text from Solstice-AI, released under Apache License 2.0. It has 262,144-token context. Its published files total 1.1 GB. It draws 554 downloads a month.

OCP Microscaling FP4 (MXFP4) format via compressed-tensors with dynamic group scaling, optimized for high throughput inference across modern accelerators.

Parameters—
Context262,144
Weights1.0 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads554

Model Card

By Solstice-AI, published under apache-2.0, revision 6d6f45ecee1b.

OCP Microscaling FP4 (MXFP4) format via compressed-tensors with dynamic group scaling, optimized for high throughput inference across modern accelerators.

Read Solstice-AI's full model card

Official Solstice-AI OCP Microscaling FP4 Suite

Original Model & GAIN Merge by DavidAU • MXFP4 Quantization & Packaging by Solstice-AI

Overview

OCP Microscaling FP4 (MXFP4) format via compressed-tensors with dynamic group scaling, optimized for high throughput inference across modern accelerators.

Serving with vLLM

vllm serve Solstice-AI/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-MXFP4 \
  --tensor-parallel-size 1 \
  --max-model-len 262144

Configuration

Architecture
Qwen3_5ForConditionalGeneration
Context length (tokens)
262,144
Layers
64
Hidden size
5,120
Feed-forward size
17,408
Attention heads
24
Key/value heads
4
Head dimension
256
Vocabulary size
248,320
Model type
qwen3_5

Identity and Version

Repository
Solstice-AI/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-MXFP4
Publisher
Solstice-AI
Task
Image and text to text
Modality
Image and text
Library
Not stated by the source
Parameters
Not stated by the source
Languages
en, zh
Revision
6d6f45ecee1bd50de4dc8ade2af9b509146616b6
First published
2026-09-11
Last updated
2026-10-15

Files and Weights

12 files, 1.1 GB in total. The weights are 2 files totalling 1.0 GB in gguf, safetensors.

Weights2 files · 1.0 GB
Configuration4 files · 4.8 KB
Tokenizer3 files · 19.6 MB
Documentation1 file · 1.3 KB
Other1 file · 51.1 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
mmproj-BF16.ggufWeights931.1 MB a7fefa002db7
model-mtp-restored.safetensorsWeights104.9 MB fbea25865ec1
config.jsonConfiguration3.9 KB —
generation_config.jsonConfiguration202 B —
preprocessor_config.jsonConfiguration390 B —
video_preprocessor_config.jsonConfiguration385 B —
README.mdDocumentation1.3 KB —
chat_template.jinjaOther51.1 KB —
.gitattributesRepository1.6 KB —
tokenizer.jsonTokenizer12.8 MB 0997f410c57a
tokenizer_config.jsonTokenizer59.3 KB —
vocab.jsonTokenizer6.7 MB —

License and Download

License
apache-2.0
Access
Open weights, no gate
Download size
1.0 GB
Download from Solstice-AI

Released by Solstice-AI through its official repository on Hugging Face. Read the license.

Built From

  • Derived from DavidAU/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored
  • Quantized from DavidAU/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored

Memory Requirements

PrecisionWeights in memory
As published1.0 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-MXFP4

Can I use Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-MXFP4 commercially?

Yes. Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-MXFP4 is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

What is Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-MXFP4's context length?

262,144 tokens, from the maximum position embeddings in its published configuration.

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