🔍 Read the full analysis: “Uncensored” DeepSeek Brings The Safety-versus-Censorship Question Home on ThorstenMeyerAI.com
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TL;DR
AtomicChat has published an edited version of DeepSeek-V4.1-Flash-1017 that it says refused 0% of harmful requests on JailbreakBench, compared with 85.2% for the base model. The figures have not been independently replicated, and the edit removes refusals across topics; its effect on the model’s political bias has not been measured. Developers say a compressed version can run with a 12 GB GPU, but also requires substantial system memory and storage.
AtomicChat has published an edited version of DeepSeek-V4.1-Flash-1017 that it says refused 0% of harmful requests on a standard safety test, compared with 85.2% for the original model. The community build is presented as runnable on a computer with a 12 GB graphics card, but the test results are self-reported, the hardware claim comes with substantial memory and storage requirements, and the edit removes refusals across topics rather than only dangerous requests.
The repository, named DeepSeek-V4.1-Flash-1017-Uncensored-GSQ-RCO-GGUF, is published under the AtomicChat account on Hugging Face. AtomicChat says the edit reduces refusals on JailbreakBench from 85.2% to 0.0% while preserving reasoning scores. Those figures have not been independently replicated. The publisher also warns that its refusal classifier reads the beginning of an answer, meaning a later, softer refusal may be counted as a successful answer.
The build combines DeepSeek’s model, compression work from ISTA-DASLab at the Institute of Science and Technology Austria, and AtomicChat’s refusal-removal edit. The lab’s Gumbel-Softmax Quantization and per-tensor bit-budget methods reduce the files needed to store the model; AtomicChat says its changes affect only some shared model components. The publisher says the large expert blocks remain as ISTA shipped them, but no outside party has verified that account.
According to the developers, Strata can run the compressed model using a single GPU with 12 GB of VRAM, with much of the model held in system memory. Their estimates also call for 46 to 64 GB of RAM, about 250 GB of downloads and performance of roughly 5 to 10 tokens per second. These are developer figures, not independent hardware tests. The repository was not gated and had 30,284 downloads in the month before November 3, according to the source report.
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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One Edit Removes Every Refusal
The central issue is that the edit is not described as a narrow safety adjustment. AtomicChat’s model card says it “removes refusals across topics” and does not preserve a smaller category of refusals. That means the same change that may remove refusals to harmful requests can also affect refusals on political subjects. Whether the edit changes the model’s political answers or underlying slant has not been measured.
For businesses, a relatively capable model that can run locally creates a potential shadow AI concern: employees could use it outside company gateways, monitoring and policy controls. Removing refusals also removes one internal brake against responses to malicious or manipulative prompts, though it does not by itself establish that a system will be compromised or cause harm. The practical concern is that local use may be harder for an organization to see and manage.
For individuals, running a model offline can offer more control over data and avoid some platform-level restrictions. It does not make the model neutral, accurate or safe. With fewer refusals, responsibility shifts more directly to the user to judge outputs and comply with applicable laws. The source report also notes that obligations under the EU AI Act depend on how a model is used, not simply on who removed its refusals; the specific obligations depend on the use case.
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From Open Weights to Local Use
DeepSeek released V4.1-Flash on September 10, 2026, followed by the V4.1-Flash-1017 update on October 17. DeepSeek’s announcement described the update as “a Pareto improvement in performance and cost”, according to the source report, without discussing safety. The model card says the weights are under the MIT License and, as reported by ThorstenMeyerAI.com, contains no acceptable-use policy.
The uncensored label itself is not new. The source report says techniques for removing refusal behavior have circulated since a 2024 research paper described refusal in chat models as tied to a “single direction.” It also reports that Hugging Face’s “abliterated” tag filter listed 12,613 models on November 3, 2026. Those figures describe the platform’s listings on that date, not a measure of model quality or usage.
What the report identifies as the change in this case is the combination of a very large open model with compression methods aimed at making local operation more accessible. It also raises a specific question about DeepSeek: earlier versions were found by U.S. government evaluators to have built-in Chinese Communist Party censorship, according to the source. That finding concerns older versions; the source does not provide a comparable evaluation of this build.
“The edit removes refusals across topics; it does not keep a narrower set of them.”
— AtomicChat, in the model card
Test Results and Bias Unchecked
The reported drop in JailbreakBench refusals and the claim that reasoning scores held are publisher-reported figures; independent replications are not available in the source material. The test description also carries a stated limitation: a refusal appearing later in an answer may not be identified by the classifier.
It is not yet clear whether the edit changes the model’s political responses, or whether any political slant in earlier DeepSeek versions remains in this build. Nor has an outside party confirmed that the model’s large expert blocks are byte-for-byte unchanged, or independently reproduced the stated performance on a 12 GB GPU. The claimed download and usage figures are a snapshot reported on November 3, not evidence of long-term adoption.
Independent Checks Will Matter
The next useful evidence would be independent testing of the claimed JailbreakBench results, including how the test handles refusals later in an answer, alongside checks of reasoning performance. Reproducing the hardware claim would also clarify the real memory, storage and speed trade-offs for people trying to run the model locally.
Evaluations of political responses would address a separate open question: whether removing refusal behavior changes those answers or leaves the model’s existing tendencies intact. Until such assessments are available, the build’s safety results, political behavior and practical performance should be treated as unverified claims from its publisher. Organizations considering local models will also need to assess how employees could use them and what oversight applies to their particular deployments.
Key Questions
What did AtomicChat publish?
It published an edited, compressed version of DeepSeek-V4.1-Flash-1017 on Hugging Face. The edit is described as removing refusals across topics.
Has the claim of 0% refusals been independently verified?
No independent replication is provided in the source report. AtomicChat says its JailbreakBench refusal figure fell from 85.2% to 0.0%, but those numbers remain self-reported and the classifier has a stated limitation.
Can it really run with a 12 GB graphics card?
The developers say Strata can run it with a 12 GB GPU, using system memory for much of the model. Their estimates also require 46 to 64 GB of RAM and about 250 GB of downloads; the performance claim has not been independently tested in the source material.
Does “uncensored” mean the model is politically neutral?
No. The edit removes refusals across topics, but its effect on the model’s political answers has not been measured. Removing refusals does not establish that the model is neutral or accurate.
Source: ThorstenMeyerAI.com
