🔍 Read the full analysis: “Uncensored” DeepSeek Runs Locally, With Safety And Censorship Linked on ThorstenMeyerAI.com
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TL;DR
AtomicChat has published a modified DeepSeek-V4.1-Flash-1017 model that it says removes refusals and can run locally using a 12 GB graphics card. Its reported safety-test results and hardware claims have not been independently replicated; running it also requires substantial system memory and storage. The edit removes refusals across topics, and its effect on the model’s political bias has not been measured.
AtomicChat has published a modified version of DeepSeek’s V4.1-Flash-1017 model that it says removes the model’s refusals and can run locally on a computer with a 12 GB graphics card. The project’s reported test results have not been independently replicated, and its own documentation says the edit removes refusals across topics, leaving open whether political bias in the model’s answers changes.
The Hugging Face repository, named DeepSeek-V4.1-Flash-1017-Uncensored-GSQ-RCO-GGUF, combines DeepSeek’s model, compression work from ISTA-DASLab at the Institute of Science and Technology Austria, and AtomicChat’s refusal-removal edit. AtomicChat says its version’s refusal rate on JailbreakBench fell from 85.2% to 0.0%, while reasoning scores held. Those figures are the publisher’s claims, not independently verified results.
The “single 12 GB GPU” description comes with significant limits. Developers say the setup needs 46 to 64 GB of system RAM, about 250 GB of downloads, and produces roughly five to 10 tokens per second in their tests. Strata, the free engine used to run the compressed model, keeps much of it in system memory; the GPU figure does not mean the model fits entirely in graphics memory or runs at high speed.
AtomicChat’s model card acknowledges that its edit removes refusals across topics rather than preserving a narrower set. It also says the refusal classifier checks the beginning of an answer, meaning a later soft refusal could be counted as an answer. The card says some model components were left unchanged, but that claim has not been checked by an independent party. The repository is available without access restrictions and is MIT-licensed.
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 Tradeoff
The development combines local operation with a large model, lowering reliance on a hosted service while also bypassing the service-level controls that can block, log or review prompts. For users, that can mean more privacy and fewer platform-imposed refusals. It does not mean the model is neutral, accurate or safe: removing a refusal mechanism does not verify the answers it gives, and AtomicChat says the edit is not selective.
For organizations, the concern described in the source is shadow AI: employees may run a capable model outside approved gateways and monitoring systems. Removing refusals also removes one internal response to some harmful or manipulative prompts, though the source does not provide evidence of a specific incident caused by this build. The source notes that EU AI Act responsibilities depend on how a system is used, not simply on who removed its refusals; the precise duties will depend on the use and applicable rules.
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Three Projects Form One Build
DeepSeek released V4.1-Flash on September 10, 2026, followed by the 1017 update on October 17. DeepSeek’s announcement described that update as “a Pareto improvement in performance and cost” and did not discuss safety. Its model card states that the weights are licensed under MIT and, according to the source, includes no acceptable-use policy or safety section.
ISTA-DASLab’s contribution is compression, not refusal removal. Its methods reduce the files needed to use the model. AtomicChat then alters the model to remove a refusal-related direction. The technique has precedents: the source says research published in 2024 linked chat-model refusals to a single direction, and that removing it has since become routine. Hugging Face’s “abliterated” tag listed 12,613 models on November 3, 2026, a count that indicates the method’s presence on the platform, not how many are widely used.
The political question is distinct from the safety-test score. The source says US government evaluators found censorship of Chinese Communist Party-related topics in older DeepSeek versions. It has not established that those findings apply unchanged to this newer model, or that AtomicChat’s edit removes political slant. AtomicChat’s own description says it does not preserve refusals by topic.
“The edit removes refusals across topics; it does not keep a narrower set of them.”
— AtomicChat’s model card
Test Results and Bias Remain Unchecked
No independent replication is cited for AtomicChat’s 85.2% to 0.0% JailbreakBench result, its claim that reasoning scores held, or the stated hardware performance. The model card’s own warning about how it classifies refusals adds a further limitation. The source also says the claim that large model components were preserved byte for byte has not been independently checked.
It remains unclear whether the edited model retains, reduces or changes political slant, including the behavior reported in older DeepSeek versions. No measurement of that question is provided. The available material also does not establish how the model performs across other safety tests, what real-world users are doing with it, or whether its local setup is practical for typical consumer PCs.
Independent Checks Are the Next Test
The next useful evidence would be independent safety evaluations that publish their methods, test more than the opening lines of answers, and distinguish harmful-request refusals from political-topic behavior. Independent checks of the model files and hardware requirements would also help establish whether AtomicChat’s technical descriptions match the build users can download.
Until those checks are available, the reported scores and performance should be treated as publisher claims. The model is already downloadable, but the source identifies no scheduled audit, official response from DeepSeek, or follow-up test date.
Key Questions
What did AtomicChat publish?
It published an edited DeepSeek-V4.1-Flash-1017 build on Hugging Face, combining the base model and compression work with an edit intended to remove refusals.
Has the model been verified to refuse zero harmful prompts?
No independent replication is cited. The 0.0% refusal figure is AtomicChat’s reported result on JailbreakBench, and its card warns that the test may miss a soft refusal later in an answer.
Does it really run on a 12 GB graphics card?
Developers say it can use a 12 GB GPU with Strata, but their stated setup also requires 46 to 64 GB of system RAM and about 250 GB of downloads. Their tests report roughly five to 10 tokens per second.
Does removing refusals remove political bias?
That has not been measured. AtomicChat says its edit removes refusals across topics; the source does not establish whether the model’s political slant changes.
Is the modified model restricted to approved users?
The source says the Hugging Face repository is not gated and is MIT-licensed. Users remain responsible for their use and for following applicable laws, according to the model card.
Source: ThorstenMeyerAI.com
