Qwythos-9B-Claude-Mythos-5-1M-abliterated
9BOther
from empero-ai/Qwythos-9B-Claude-Mythos-5-1M
↓ 66.3K♥ 22712 repos
Qwythos-9B-Claude-Mythos-5-1M
Qwythos-9B-Claude-Mythos-5-1M is a abliterated and uncensored variant of empero-ai/Qwythos-9B-Claude-Mythos-5-1M, published on Hugging Face by empero-ai. It is 9B parameters, single consumer GPU class and apache-2.0 licence. It is distributed across 103 repositories in GGUF, Transformers, NVFP4 and AWQ formats, totalling 235.5K downloads.
Specification
- Model name
- Qwythos-9B-Claude-Mythos-5-1M
- Source repository
- empero-ai/Qwythos-9B-Claude-Mythos-5-1M
- Base model
- empero-ai/Qwythos-9B-Claude-Mythos-5-1M
- Publisher
- empero-ai
- Parameters
- 9B
- VRAM required
- ~6.2 GB at Q4_K_M, 4k context (estimated) — runs on 8 GB cards
- Hardware class
- 4B – 10B — single consumer GPU
- Licence
- apache-2.0
- Task
- Text generation
- Context window
- Not documented
- Ablation scope
- Not stated by the publisher
- Formats available
- GGUF, Transformers, NVFP4, AWQ, MLX, GGUF (imatrix)
- First indexed
- 19 Jun 2026
- Last updated
- 28 Oct 2026
Ablation technique
How Qwythos-9B-Claude-Mythos-5-1M was modified, and what that implies.
Abliteration + uncensored fine-tune
Directional ablation combined with additional fine-tuning on unfiltered data, so behaviour diverges from the base model beyond refusal removal alone.
Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.
From the publisher’s model card
“Qwythos-9B is a full-parameter reasoning model built on top of a deeply uncensored Qwen3.5-9B base and post-trained on over 500 million tokens of high-quality Claude Mythos and Claude Fable traces, with chain-of-thought generated in-house by Empero AI's internal tool rethink.”
Running it
Commands are templates — confirm the exact repository and quant file before use.
llama.cpp / GGUF
hf download empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF --local-dir ./qwythos-9b-claude-mythos-5-1m
llama-cli -m ./qwythos-9b-claude-mythos-5-1m/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "empero-ai/Qwythos-9B-Claude-Mythos-5-1M"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve empero-ai/Qwythos-9B-Claude-Mythos-5-1M --trust-remote-codeDownloads and variants (102)
Every published repository of Qwythos-9B-Claude-Mythos-5-1M, including quantised re-releases by other authors.
Security-team assessment
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
- Qwythos-9B-Claude-Mythos-5-1M will attempt offensive-security prompts that a hosted commercial model declines, which is what makes it usable for red-team corpus generation and for measuring what an unaligned model of this class produces.
- Capability is inherited from empero-ai/Qwythos-9B-Claude-Mythos-5-1M, not added by ablation — at 9B parameters, expect a small model’s reasoning and a high error rate on exploit detail.
- The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
- This release adds fine-tuning on unfiltered data, so its behaviour diverges from the base model beyond refusal removal — differences you measure cannot be attributed to ablation alone.
- Declared licence is apache-2.0, but the terms that bind you are empero-ai/Qwythos-9B-Claude-Mythos-5-1M’s — a re-release cannot grant more than its parent.
Handling: run it isolated, put moderation in front of it if anyone outside your team can reach it, and verify the weights before loading — these are third-party artifacts. Full handling and licence guidance.
Metadata for Qwythos-9B-Claude-Mythos-5-1M is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with empero-ai, and does not independently verify publisher claims. See responsible use.