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TL;DR
AtomicChat has published a modified DeepSeek-V4.1-Flash-1017 model and reports that its refusal rate on JailbreakBench fell from 85.2% to 0%. Those results have not been independently replicated. The build is presented as runnable with a 12 GB graphics card, but developers say it also needs substantial system memory and storage; its political bias and real-world safety remain untested.
AtomicChat has published a modified version of DeepSeek-V4.1-Flash-1017 that it says refused 0% of harmful requests in a standard safety test, compared with 85.2% for the original. The figures are the publisher’s own and have not been independently replicated. The release matters because its developers say the very large model can run locally with a 12 GB graphics card, potentially putting an altered, less restrictive system outside the safeguards of hosted AI services.
The Hugging Face repository, named DeepSeek-V4.1-Flash-1017-Uncensored-GSQ-RCO-GGUF, combines DeepSeek’s model with compression work from ISTA-DASLab at the Institute of Science and Technology Austria and a refusal-removal edit attributed to AtomicChat. AtomicChat says the JailbreakBench refusal rate fell from 85.2% to 0.0% while reasoning scores held. No independent testing of those results is cited in the supplied source material.
The project’s model card says the edit removes refusals across topics, rather than preserving refusals for some categories. It also warns that its refusal classifier looks at the beginning of an answer, so a refusal later in the response can be missed. The publisher says some model components were left unchanged, but that claim has not been checked externally.
The single-GPU description has significant qualifications. According to the developers’ tests, running the compressed model with the Strata engine requires 46–64 GB of system RAM, about 250 GB of downloads and delivers roughly 5–10 tokens per second. Those performance and hardware figures are also developer-reported, not independent measurements. The base model is MIT-licensed, and its model card has no acceptable-use policy, according to the source material.
Infographic 01 · From a paper to a gaming PC
“Uncensored” is two years old. The new part is the size.
How a 2024 research finding, an MIT licence, a compression lab and a hobby engine put a 763-billion-parameter model on one 12 GB graphics card.
- 15 Aug 2023China’s generative AI rules take effectServices must “(u)phold the Core Socialist Values”
- Jun 2024Refusal is “a single direction”Shown across 13 open chat models up to 72B; removing it stops refusals
- Sep 2025US evaluators: censorship sits in the weightsNIST CAISI on older DeepSeek models (R1, R1-0528, V3.1), not V4.1
- 10 Sep 2026DeepSeek-V4.1-Flash released under MITFirst uncensored forks within hours, per Tech Insider
- 17 Oct 2026Update V4.1-Flash-1017Weights on Hugging Face and ModelScope; no safety statement
- 24 Oct 2026A free hobby engine adds the modelStrata 0.2.4: one 12 GB GPU, the rest streamed from RAM and SSD
- 3 Nov 202612,613 models tagged “abliterated”Hugging Face tag filter; several V4.1-Flash builds on page one
Hardware figures from the Strata release notes and the ISTA-DASLab model card (publisher figures). “Consumer hardware” here means a well-equipped gaming or workstation PC, not a laptop.
Sources: DeepSeek model card, DeepSeek, 17 Oct 2026, Arditi et al., arXiv 2406.11717 (2024), NIST CAISI, 30 Sep 2025 (older models), FPF on China's Interim Measures, Tech Insider, Strata release notes 0.2.4/0.2.5 (24/25 Oct 2026), ISTA-DASLab model card, Hugging Face model search (3 Nov 2026).
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Local Access Changes the Safety Picture
A model running locally can offer users more privacy than sending prompts to a hosted service, and may avoid restrictions imposed by a platform. But local operation also means an employer’s usual controls—such as approved gateways, usage logs and policy checks—may not see the interaction. For companies, the immediate concern is shadow AI: staff could run a capable model on a desktop beyond the organization’s oversight.
Removing refusals does not establish that the model is accurate, politically neutral or safe for a particular use. It removes one layer of response behavior, while responsibility for checking outputs and controlling use shifts toward the operator. The source article also notes that legal obligations under the EU AI Act depend on how a system is used, not simply on who altered its refusal behavior; companies should not treat a local installation as a compliance exemption.
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How the Three-Part Build Works
DeepSeek released V4.1-Flash on September 10, 2026, followed by the 1017 update on October 17. The company described that update as a performance-and-cost improvement, according to the source, but did not make a safety claim in that announcement. Its weights are available under the MIT License.
The second component is compression research from ISTA-DASLab. Its quantization methods reduce the model’s storage footprint; the lab’s work is distinct from AtomicChat’s refusal edit and is not described as a safety intervention. Strata, a free engine developed outside a company, uses system memory to run a large mixture-of-experts model while relying on a single GPU for processing.
Removing refusal behavior is not a new technique. The source reports that research published in 2024 linked refusal behavior in chat models to a direction within a model, and that Hugging Face’s “abliterated” filter listed 12,613 models on November 3, 2026. That is a count at a particular time, not a measure of model quality or adoption. The reported novelty here is the combination of a large model, local hardware claims and a refusal-removal edit.
“The edit removes refusals across topics; it does not keep a narrower set of them.”
— AtomicChat, in the model card
Tests, Bias and Hardware Need Checking
The reported 0.0% refusal rate, preserved reasoning scores, component-level changes and local performance figures have not been independently replicated in the source material. A benchmark result also cannot establish how a model will behave across prompts, languages or real-world settings.
It is not clear whether removing refusal behavior changes the political framing of answers. The source says US government evaluators found built-in Chinese Communist Party censorship in older DeepSeek versions, but it provides no corresponding evaluation of this modified build. The relationship between political refusals and refusals on dangerous requests is therefore a concern raised by the edit’s scope, not a verified finding about the new model’s answers.
The “12 GB GPU” description should not be read as a claim that a typical computer can run the model without constraints: reported requirements include up to 64 GB of system RAM, around 250 GB of downloads and relatively slow output. Independent hardware tests and a review of the modified files are not provided.
Independent Replication Is the Next Test
The next useful checks would be independent runs of the safety and reasoning benchmarks, verification of the published model files, and tests of political bias and answer quality across a broader set of prompts. Hardware reviewers could also establish whether the stated memory, storage and speed requirements hold on commonly available systems.
Until those checks are available, users and organizations should treat the release’s headline results as publisher claims, not established performance. Companies considering local models can review their device policies, approved AI tools and monitoring practices; users should remember that removing a refusal does not make an answer reliable or lawful to act on.
Key Questions
What did AtomicChat release?
It published a modified DeepSeek-V4.1-Flash-1017 model on Hugging Face. The build combines DeepSeek’s model, compression methods from ISTA-DASLab and an AtomicChat edit intended to reduce refusals.
Has the reported 0% refusal rate been independently confirmed?
No independent replication is cited. The 0.0% figure is AtomicChat’s report of its JailbreakBench result, not a verified finding from an outside evaluator.
Can it really run with a 12 GB graphics card?
That is the developers’ claim, with substantial additional requirements. Their reported setup uses 46–64 GB of system RAM, roughly 250 GB of downloads and produces about 5–10 tokens per second.
Does removing refusals make the model politically neutral?
That has not been established. The source says the edit removes refusals across topics, but the modified model’s political bias has not been measured.
What should companies take away from the release?
A locally run model may operate outside company gateways, logs and policy controls. Organizations should treat it as a potential shadow-AI and governance issue, while evaluating legal duties based on their actual use of the system.
Source: ThorstenMeyerAI.com
