# Qwen3.8-27B-OBLITERATED by OBLITERATUS: Open-Weight Model
Source: https://savrn.com/models/qwen3-8-27b-obliterated
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

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## Runs On

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

| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
| --- | --- | --- | --- | --- | --- |
| 16-bit | 55.6 GB | 66.7 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |
| 8-bit | 27.8 GB | 33.3 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |
| 4-bit | 13.9 GB | 16.7 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/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](https://savrn.com/ai-index/pricing/gpus), read Oct 23, 2026.

[Qwen3.8-27B-OBLITERATED on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/qwen3-8-27b-obliterated/gpus)

## SAVRN's Notes on Qwen3.8-27B-OBLITERATED

Hardware first: 27.8B parameters, 66.7 GB needed at 16-bit, 33.3 GB at 8-bit, 16.7 GB at 4-bit — any of them fits one MI300X with 192 GB at $1.85 an hour, with the 262,144-token window the real memory consumer once you fill it. The download is heavy: 70 files, 239.7 GB, in safetensors and GGUF. This is a repack of Qwen/Qwen3.8-27B, versioned V3 Deep Liberation, and it pulls 1.1M downloads a month, so operators are clearly running it.

What you are buying is behavior, and the publisher prices it openly: its own 0-shot lm-eval table shows stock Qwen3.8-27B at 84.5% MMLU against 82.3% for V3, a self-reported 2.1-point drop, alongside 20 of 20 working code generations and 7 of 8 advanced real-world prompts. Apache 2.0 allows the use; it does not decide who in your organization may prompt a model built to skip refusals — that policy is yours to write. No evaluations beyond the card's and no hosted prices appear on the page.

SAVRN Research

## Model Card

By OBLITERATUS, published under apache-2.0, revision a58c3b53b3ce.

Genuinely uncensored. Real answers, not safety lectures. Near-stock capability.

### V3: Deep Liberation

V3 applies iterative refinement on top of V2's complementary blend, with targeted corpus expansion. The result: genuine liberation — not just removal of hard refusals but elimination of safety-lecture deflections.

|  | Stock Qwen3.8-27B | V1 | V2 | V3 |
| --- | --- | --- | --- | --- |
| MMLU (lm-eval, 0-shot) | 84.5% (n=5700) | 81.4% | 84.3% | 82.3% |
| vs stock | — | -6.0pp | -0.3pp | -2.1pp |
| Liberation quality | refuses | hard refusals removed | soft deflections remain | genuinely answersYes |
| Cyber/code tasks (20 prompts) | refuses | untested | untested | 20/20 with working codeYes |
| Advanced real-world | 5/8 | untested | 7/8 | 7/8 |
| Thinking mode | Yes | No | (refuses) |  |

V3 highlights: - Genuinely answers restricted queries — provides real substance instead of safety lectures - 20/20 on code generation tasks — functional implementations, not disclaimers - Thinking ON compatible — no refusals in either thinking mode - Honest scoring — every response manually audited for real substance, not just absence of "I cannot" - -2.1pp MMLU — modest capability cost for genuine liberation

[Read the full model card (1,321 words)](https://savrn.com/models/qwen3-8-27b-obliterated/card)

## 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

OBLITERATUS/Qwen3.8-27B-OBLITERATED

Publisher

OBLITERATUS

Task

Text generation

Modality

Text

Library

mlx

Parameters

27.8B parameters

Languages

mlx, red-team

Revision

a58c3b53b3ce71551eafde2ed5ec8df48e0f4ff8

First published

2026-08-19

Last updated

2026-08-24

## Files and Weights

70 files, 239.7 GB in total. The weights are 55 files totalling 239.7 GB in gguf, safetensors.

Weights55 files · 239.7 GB

Configuration7 files · 125.7 KB

Tokenizer4 files · 22.9 MB

Documentation2 files · 22.8 KB

Other1 file · 506 B

Repository1 file · 2.3 KB

Every file

| File | Type | Size | SHA-256 |
| --- | --- | --- | --- |
| Qwen3.8-27B-OBLITERATED-IQ4_XS.gguf | Weights | 15.4 GB | f269deda48b0 |
| Qwen3.8-27B-OBLITERATED-Q2_K.gguf | Weights | 10.9 GB | 55f457543858 |
| Qwen3.8-27B-OBLITERATED-Q3_K_M.gguf | Weights | 13.5 GB | 2d088b821df3 |
| Qwen3.8-27B-OBLITERATED-Q4_K_M.gguf | Weights | 16.8 GB | 1f74330b211a |
| Qwen3.8-27B-OBLITERATED-Q5_K_M.gguf | Weights | 19.5 GB | 87a69c852388 |
| Qwen3.8-27B-OBLITERATED-Q6_K.gguf | Weights | 22.4 GB | 3535d4a15b75 |
| Qwen3.8-27B-OBLITERATED-Q8_0.gguf | Weights | 29.0 GB | afa839b2fa5b |
| mmproj-model-bf16.gguf | Weights | 931.1 MB | e484e3b7e907 |
| model-00001-of-00018.safetensors | Weights | 4.0 GB | 12cd93998661 |
| model-00001-of-00028.safetensors | Weights | 2.5 GB | 92ed1c3e6826 |
| model-00002-of-00018.safetensors | Weights | 3.0 GB | c6d11ab4027a |
| model-00002-of-00028.safetensors | Weights | 1.9 GB | 1b73f760a28a |
| model-00003-of-00018.safetensors | Weights | 2.5 GB | 92ed1c3e6826 |
| model-00003-of-00028.safetensors | Weights | 1.9 GB | 41f6c3912251 |
| model-00004-of-00018.safetensors | Weights | 4.0 GB | f3c7c94524f1 |
| model-00004-of-00028.safetensors | Weights | 1.9 GB | b08e9be18196 |
| model-00005-of-00018.safetensors | Weights | 2.1 GB | c4b378576714 |
| model-00005-of-00028.safetensors | Weights | 2.0 GB | 360ea4390ae3 |
| model-00006-of-00018.safetensors | Weights | 4.0 GB | b529087c1b78 |
| model-00006-of-00028.safetensors | Weights | 1.9 GB | 40838e78d482 |
| model-00007-of-00018.safetensors | Weights | 2.1 GB | 934f725ad88f |
| model-00007-of-00028.safetensors | Weights | 1.9 GB | a14dff178db4 |
| model-00008-of-00018.safetensors | Weights | 4.0 GB | 0f88c5462313 |
| model-00008-of-00028.safetensors | Weights | 1.9 GB | 3839575cd9b5 |
| model-00009-of-00018.safetensors | Weights | 2.1 GB | e4f10056c6e6 |
| model-00009-of-00028.safetensors | Weights | 1.9 GB | f6bc535a7b91 |
| model-00010-of-00018.safetensors | Weights | 4.0 GB | e2569ca8c91a |
| model-00010-of-00028.safetensors | Weights | 1.9 GB | 4f5423a5997b |
| model-00011-of-00018.safetensors | Weights | 2.1 GB | 49c1ad6d9bc1 |
| model-00011-of-00028.safetensors | Weights | 1.9 GB | f66eea52fa1c |
| model-00012-of-00018.safetensors | Weights | 4.0 GB | 978741e702a5 |
| model-00012-of-00028.safetensors | Weights | 1.9 GB | 28204de1451f |
| model-00013-of-00018.safetensors | Weights | 2.1 GB | ed751392f086 |
| model-00013-of-00028.safetensors | Weights | 2.0 GB | 744952d16080 |
| model-00014-of-00018.safetensors | Weights | 4.0 GB | 2b8a5053af4e |
| model-00014-of-00028.safetensors | Weights | 1.9 GB | bde0a5a92e2c |
| model-00015-of-00018.safetensors | Weights | 2.1 GB | 1f9900187317 |
| model-00015-of-00028.safetensors | Weights | 1.9 GB | 8210cf2fa43a |
| model-00016-of-00018.safetensors | Weights | 4.0 GB | de00c29552e3 |
| model-00016-of-00028.safetensors | Weights | 1.9 GB | 486a4a08741d |
| model-00017-of-00018.safetensors | Weights | 2.1 GB | 5b6141dc174b |
| model-00017-of-00028.safetensors | Weights | 1.9 GB | f10fa5ffcc46 |
| model-00018-of-00018.safetensors | Weights | 3.4 GB | dbbd8bd279bc |
| model-00018-of-00028.safetensors | Weights | 1.9 GB | 649108a637c5 |
| model-00019-of-00028.safetensors | Weights | 1.9 GB | 7102932fff7b |
| model-00020-of-00028.safetensors | Weights | 1.9 GB | 46cee6c2d138 |
| model-00021-of-00028.safetensors | Weights | 2.0 GB | 92a8def54809 |
| model-00022-of-00028.safetensors | Weights | 1.9 GB | 01b504170b88 |
| model-00023-of-00028.safetensors | Weights | 1.9 GB | 8a062b064c58 |
| model-00024-of-00028.safetensors | Weights | 1.9 GB | 1293b0d48bdb |
| model-00025-of-00028.safetensors | Weights | 1.9 GB | 6e7b919f8a64 |
| model-00026-of-00028.safetensors | Weights | 1.9 GB | d3c1d1d66a52 |
| model-00027-of-00028.safetensors | Weights | 2.5 GB | 2574026178e6 |
| model-00028-of-00028.safetensors | Weights | 1.1 GB | 916afba536e0 |
| model-extra-00001-of-00001.safetensors | Weights | 1.8 GB | 85003d3250af |
| abliteration_metadata.json | Configuration | 2.9 KB | — |
| config.json | Configuration | 3.7 KB | — |
| generation_config.json | Configuration | 165 B | — |
| hard_negative_residue.json | Configuration | 3.9 KB | — |
| model.safetensors.index.json | Configuration | 114.3 KB | — |
| preprocessor_config.json | Configuration | 390 B | — |
| video_preprocessor_config.json | Configuration | 385 B | — |
| LICENSE | Documentation | 11.5 KB | — |
| README.md | Documentation | 11.3 KB | — |
| chat_template.jinja | Other | 506 B | — |
| .gitattributes | Repository | 2.3 KB | — |
| merges.txt | Tokenizer | 3.4 MB | — |
| tokenizer.json | Tokenizer | 12.8 MB | 0997f410c57a |
| tokenizer_config.json | Tokenizer | 7.7 KB | — |
| vocab.json | Tokenizer | 6.7 MB | — |

## License and Download

License

apache-2.0

Access

Open weights, no gate

Download size

239.7 GB

[Download from OBLITERATUS](https://huggingface.co/OBLITERATUS/Qwen3.8-27B-OBLITERATED)

Released by OBLITERATUS through its official repository on Hugging Face. [Read the license](https://www.apache.org/licenses/LICENSE-2.0).

## Built From

- Derived from [Qwen/Qwen3.8-27B](https://savrn.com/models/qwen3-8-27b)
- Quantized from [Qwen/Qwen3.8-27B](https://savrn.com/models/qwen3-8-27b)

## Memory Requirements

| Precision | Weights in memory |
| --- | --- |
| As published | 239.7 GB |
| 16-bit | 55.6 GB |
| 8-bit | 27.8 GB |
| 4-bit | 13.9 GB |

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

## Questions About Qwen3.8-27B-OBLITERATED

### How much GPU memory does Qwen3.8-27B-OBLITERATED 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 Qwen3.8-27B-OBLITERATED 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.

### Can I use Qwen3.8-27B-OBLITERATED commercially?

Yes. Qwen3.8-27B-OBLITERATED 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-OBLITERATED's context length?

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

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## OBLITERATUS

[All models and datasets](https://savrn.com/model-publishers/obliteratus)

## Versions

- [a58c3b53b3ce](https://savrn.com/models/qwen3-8-27b-obliterated/versions/a58c3b53b3ce) · current 2026-09-24

## Explore More

- [All text generation models](https://savrn.com/models/tasks/text-generation)
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## Source

- Repository metadata, read 2026-10-19.
- [Hugging Face record](https://huggingface.co/OBLITERATUS/Qwen3.8-27B-OBLITERATED)
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