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Open-weight model · Image and text to text

Swift-Qwen3.8-27B-Uncensored-MTP

by AJ Gazin ajgazin/Swift-Qwen3.8-27B-Uncensored-MTP

Swift-Qwen3.8-27B-Uncensored-MTP is an open-weight model for image and text to text from AJ Gazin, released under other. It has 27.8B parameters and a 262,144-token context. At 16-bit it needs about 66.7 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index. It draws 833 downloads a month.

An abliterated Swift-Qwen3.8-27B, UkisAI's reasoning-efficient fine-tune of Qwen3.8-27B. It applies the single-direction refusal ablation of (Arditi et al. 2024), with orcarouter's own direction, to Swift's weights.

Parameters27.8B
Context262,144
Weights55.6 GB
Licenseother
AccessOpen weights
Monthly Downloads833

Runs On

What it takes to serve Swift-Qwen3.8-27B-Uncensored-MTP (27.8B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso fits
16-bit 55.6 GB 66.7 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 27.8 GB 33.3 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 13.9 GB 16.7 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Sep 25, 2026.

Swift-Qwen3.8-27B-Uncensored-MTP on every accelerator the SAVRN Index prices, at every precision

Model Card

An abliterated Swift-Qwen3.8-27B, UkisAI's reasoning-efficient fine-tune of Qwen3.8-27B. It applies the single-direction refusal ablation of (Arditi et al. 2024), with orcarouter's own direction, to Swift's weights. The vision tower is untouched and the MTP head is kept and edited consistently, so self-speculative decoding works. GGUF (llama.cpp, Unsloth-dynamic Q2 to Q8) and NVFP4 (vLLM, SGLang). The same edit on Swift 1.5 is All four rows are our measurements with Heretic's built-in evaluation (evaluatemodel, BF16): keyword-based refusal detector. the original model. - Thinking is closed immediately with a response prefix ("\n \n\n"), so answers are scored, not reasoning. - Refusal counts…

Excerpt from the card by AJ Gazin, licensed other.

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
ajgazin/Swift-Qwen3.8-27B-Uncensored-MTP
Publisher
AJ Gazin
Task
Image and text to text
Modality
Image and text
Library
transformers
Parameters
27.8B parameters
Languages
mtp
Revision
5a6e1174d6be421b2d4f781d147f380609131834
First published
2026-09-15
Last updated
2026-09-25

Files and Weights

35 files, 55.6 GB in total. The weights are 19 files totalling 55.6 GB in pt, safetensors.

Weights19 files · 55.6 GB
Configuration8 files · 202.3 KB
Tokenizer4 files · 22.9 MB
Documentation1 file · 6.6 KB
Other2 files · 13.0 KB
Repository1 file · 1.7 KB
Every file
FileTypeSizeSHA-256
abliteration/r.ptWeights21.8 KB f99121055e90
model-00001-of-00018.safetensorsWeights4.0 GB 44f4600d26d1
model-00002-of-00018.safetensorsWeights3.0 GB 516e9f19f0c8
model-00003-of-00018.safetensorsWeights2.5 GB 2f75671f82af
model-00004-of-00018.safetensorsWeights4.0 GB 2cb4f5f5e2b5
model-00005-of-00018.safetensorsWeights2.1 GB 900001a1de3b
model-00006-of-00018.safetensorsWeights4.0 GB d4d5278e2332
model-00007-of-00018.safetensorsWeights2.1 GB dfe08ea92a77
model-00008-of-00018.safetensorsWeights4.0 GB dad9cb708077
model-00009-of-00018.safetensorsWeights2.1 GB d488d56ae853
model-00010-of-00018.safetensorsWeights4.0 GB 8c1abb9d5fe8
model-00011-of-00018.safetensorsWeights2.1 GB 6318a4512ffa
model-00012-of-00018.safetensorsWeights4.0 GB ff89dab16a34
model-00013-of-00018.safetensorsWeights2.1 GB a20e6c8da4ae
model-00014-of-00018.safetensorsWeights4.0 GB af38673a26bc
model-00015-of-00018.safetensorsWeights2.1 GB ac890c6697b4
model-00016-of-00018.safetensorsWeights4.0 GB f40e708d971d
model-00017-of-00018.safetensorsWeights2.1 GB a7320fa42369
model-00018-of-00018.safetensorsWeights3.4 GB 1fb2ee8c1de7
abliteration.jsonConfiguration8.1 KB —
abliteration/orca_tools.pyConfiguration22.4 KB —
abliteration/recover.jsonConfiguration54.3 KB —
config.jsonConfiguration4.3 KB —
generation_config.jsonConfiguration221 B —
model.safetensors.index.jsonConfiguration112.2 KB —
preprocessor_config.jsonConfiguration390 B —
video_preprocessor_config.jsonConfiguration385 B —
README.mdDocumentation6.6 KB —
abliteration/orca.shOther4.0 KB —
chat_template.jinjaOther9.0 KB —
.gitattributesRepository1.7 KB —
merges.txtTokenizer3.4 MB —
tokenizer.jsonTokenizer12.8 MB 0997f410c57a
tokenizer_config.jsonTokenizer17.9 KB —
vocab.jsonTokenizer6.7 MB —

License and Download

License
other
Access
Open weights, no gate
Download size
55.6 GB
Download from AJ Gazin

Released by AJ Gazin through its official repository on Hugging Face. Read the license.

Built From

Memory Requirements

PrecisionWeights in memory
As published55.6 GB
16-bit55.6 GB
8-bit27.8 GB
4-bit13.9 GB

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

Built on This Model

Questions About Swift-Qwen3.8-27B-Uncensored-MTP

How much GPU memory does Swift-Qwen3.8-27B-Uncensored-MTP need?

About 66.7 GB at 16-bit and 16.7 GB at 4-bit: the weights (27.8B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run Swift-Qwen3.8-27B-Uncensored-MTP on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

What license is Swift-Qwen3.8-27B-Uncensored-MTP released under?

other, as its publisher declares it. Read the license text before commercial use.

What is Swift-Qwen3.8-27B-Uncensored-MTP's context length?

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

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