Spark-X2.6-4B-abliterated-FIT
4BOther
from XHToken/Spark-X2.6-4B
↓ 38.4K♥ 31
Spark-X2.6-4B-uncensored
Spark-X2.6-4B-uncensored is a abliterated and uncensored variant of XHToken/Spark-X2.6-4B, published on Hugging Face by electroglyph. It is 4B parameters, single consumer GPU class and apache-2.0 licence. It is distributed across 5 repositories in GGUF, Transformers and GGUF (imatrix) formats, totalling 7.2K downloads.
Specification
- Model name
- Spark-X2.6-4B-uncensored
- Source repository
- electroglyph/Spark-X2.6-4B-uncensored
- Base model
- XHToken/Spark-X2.6-4B
- Publisher
- electroglyph
- Parameters
- 4B
- VRAM required
- ~3.2 GB at Q4_K_M, 4k context (estimated) — runs on 4 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, GGUF (imatrix)
- First indexed
- 23 Oct 2026
- Last updated
- 26 Oct 2026
Ablation technique
How Spark-X2.6-4B-uncensored 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
“A little over a month has passed since Spark-X2.5. In the rapidly evolving world of AI agents, that is enough time to rethink, refine, and move the frontier forward. Building on the Spark-X2.5-4B, we introduce Spark-X2.6-4B, the latest generation of our compact, general-purpose language models for on-device deployment.”
Running it
Commands are templates — confirm the exact repository and quant file before use.
Ollama (publisher-documented)
ollama run SparkLLM/Spark-X2.6-4Bllama.cpp / GGUF
hf download mradermacher/Spark-X2.6-4B-uncensored-i1-GGUF --local-dir ./spark-x2.6-4b-uncensored
llama-cli -m ./spark-x2.6-4b-uncensored/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "electroglyph/Spark-X2.6-4B-uncensored"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve electroglyph/Spark-X2.6-4B-uncensored --trust-remote-codeDownloads and variants (4)
Every published repository of Spark-X2.6-4B-uncensored, including quantised re-releases by other authors.
| Repository | Format | Downloads |
|---|---|---|
| mradermacher/Spark-X2.6-4B-uncensored-i1-GGUF | GGUF (imatrix) | 3.6K |
| mradermacher/Spark-X2.6-4B-uncensored-GGUF | GGUF | 2.7K |
| electroglyph/Spark-X2.6-4B-uncensoredsource | Transformers | 438 |
| OpenIntelligenceNet/Spark-X2.6-4B-Uncensored-GGUF | GGUF | 414 |
Security-team assessment
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
- Spark-X2.6-4B-uncensored 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 XHToken/Spark-X2.6-4B, not added by ablation — at 4B 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 XHToken/Spark-X2.6-4B’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 Spark-X2.6-4B-uncensored is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with electroglyph, and does not independently verify publisher claims. See responsible use.