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TL;DR
AtomicChat has published an edited version of DeepSeek-V4.1-Flash-1017 and says its refusal rate on JailbreakBench fell from 85.2% to 0%. Developers also say a compressed build can run using a 12 GB graphics card, but it requires 46–64 GB of system RAM and has not been independently tested. The edit removes refusals across topics, and it is unclear whether it changes the model’s political bias.
AtomicChat has published an edited version of DeepSeek-V4.1-Flash-1017 that it says can run on a PC with a 12 GB graphics card and refused none of the harmful prompts in its reported safety test. The result combines model compression with a separate edit that removes refusals, but the performance and test figures are self-reported and not independently replicated.
The Hugging Face repository, titled DeepSeek-V4.1-Flash-1017-Uncensored-GSQ-RCO-GGUF, brings together DeepSeek’s open model weights, 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 results are the publisher’s figures, not independently confirmed findings.
The 12 GB figure refers to graphics-card memory, not the whole computer’s memory or the model’s full storage needs. According to the developers’ tests, running the compressed model also requires 46–64 GB of system RAM and about 250 GB of downloads. They report speeds of roughly 5 to 10 tokens per second. The free Strata engine keeps much of the model in system memory; the supplied source does not include independent testing of these operating figures.
AtomicChat says the edit removes refusals “across topics” rather than retaining a narrower set. The publisher describes the change as removing a direction associated with refusal from the model. It also says the model’s large expert blocks were left as ISTA-DASLab supplied them, while acknowledging that outsiders have not verified the changes. The repository is openly available on Hugging Face and uses the MIT license, according to its model card.
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, Fewer Built-In Brakes
The development lowers the hardware barrier to experimenting with a very large open-weight model, but it does not make running it effortless: the reported setup still needs substantial system RAM, storage and specialized software. If the figures hold, a capable model could be used locally rather than through a hosted service, reducing reliance on a provider and potentially keeping prompts on a user’s computer.
That same local control can put use beyond an organization’s usual monitoring. The source describes a possible shadow AI risk: a desktop model operating outside company gateways, logs and policies. With refusals removed, users also lose one internal safeguard against harmful requests and prompt injection. These are risk considerations, not evidence that the model has caused a specific incident.
The edit raises a separate question about political content. The source says US government evaluators found built-in Chinese Communist Party censorship in older DeepSeek versions. AtomicChat’s change removes refusals across topics, but no measurements are provided showing whether it alters political bias or the model’s answers on sensitive subjects. A model described as “uncensored” is not thereby neutral, accurate or free of other biases.
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Three Projects Behind the Build
DeepSeek released V4.1-Flash on September 10, 2026, followed by the 1017 update on October 17, according to the source. DeepSeek’s announcement described the update as “a Pareto improvement in performance and cost” and did not discuss safety. The model card lists an MIT license and, as reported in the source, has no safety section or acceptable-use policy.
The smaller hardware claim depends on separate compression work. ISTA-DASLab’s methods reduce the model’s storage requirements; the lab’s work is distinct from AtomicChat’s decision to remove refusals. Strata, an open-source engine, is described as running the compressed model with one 12 GB GPU while placing other model data in system memory. The source says the model and related files require about 250 GB of downloads.
Removing refusals from language models is not itself new. The source reports that Hugging Face’s “abliterated” tag filter listed 12,613 models on November 3, 2026. That count is a snapshot of tagged models, not a measure of downloads, use or safety effects. The claimed significance of this release is the combination of a large model, consumer hardware and a broad refusal-removal edit.
“The edit removes refusals across topics; it does not keep a narrower set of them.”
— AtomicChat, in its model card
Testing and Bias Remain Unverified
No independent replication is provided for AtomicChat’s 0.0% refusal figure, its reported preservation of reasoning scores, or the hardware performance claims. The model card itself cautions that its refusal classifier examines the start of an answer, so a later soft refusal can be counted as an answer. The supplied source also says that not every model rung cleared every gate and that some were published as measured.
It is not clear whether removing the refusal-related direction changes the model’s political bias, factual accuracy or behavior beyond the tested prompts. The cited censorship findings concern older DeepSeek versions; the source does not establish how the 1017 build responds to political questions. Nor does it provide an external audit confirming that the model blocks AtomicChat describes as untouched were preserved byte for byte.
Independent Checks Are the Next Test
The next useful developments would be independent tests of the refusal and reasoning results, along with reproducible measurements of setup requirements and speed on the specified hardware. Tests would also need to examine political responses and the model’s behavior beyond the opening lines of an answer, given the limitation AtomicChat disclosed.
For organizations, the release puts attention on whether locally run models are covered by their access controls and policies. The source says obligations under the EU AI Act depend on how a model is used, not simply on who removed its refusals. The material does not provide a legal assessment of a specific deployment. For now, the reported capabilities and risks should be treated as claims pending independent evaluation.
Key Questions
What did AtomicChat publish?
It published an edited DeepSeek-V4.1-Flash-1017 build on Hugging Face. The build combines DeepSeek’s model, third-party compression work and AtomicChat’s refusal-removal edit.
Does it really run with a 12 GB graphics card?
The developers say it can use a single 12 GB GPU, with much of the model held in system memory. Their reported setup also needs 46–64 GB of RAM and about 250 GB of downloads; these claims have not been independently verified in the supplied material.
What does the 0% refusal claim mean?
AtomicChat says its build refused 0% of prompts in its reported JailbreakBench test, compared with 85.2% for the prior figure it cites. The result is self-reported, and the publisher says its classifier can miss a soft refusal that appears later in an answer.
Does “uncensored” mean the model is politically neutral?
No such finding is provided. The edit is described as removing refusals across topics, but the source says political bias has not been measured for this build. Removing refusals does not establish that answers are neutral or accurate.
Have the safety and performance claims been independently confirmed?
The supplied source reports no independent replication of AtomicChat’s test results, hardware claims or account of which model components were changed. Those points remain unverified.
Source: ThorstenMeyerAI.com
