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Nvidia releases quantized DeepSeek-V4.1-Flash-1017; uncensored version also emerges

By PulseAugur Editorial · [3 sources] ·

Nvidia has released a quantized version of DeepSeek AI's DeepSeek-V4.1-Flash-1017 model, optimized for commercial applications and featuring a multimodal Mixture-of-Experts architecture with Compressed Sparse Attention 2. This version, available on Hugging Face, supports context lengths up to one million tokens and is designed to run efficiently on Nvidia hardware, including the Blackwell platform. Separately, a community effort has produced an uncensored version of DeepSeek-V4.1-Flash-1017, which significantly reduces refusal rates while maintaining performance on benchmarks like MMLU and GPQA, and is available for users with 12GB of VRAM. AI

IMPACT Quantized models accelerate deployment for commercial applications, while uncensored versions offer greater flexibility for specific use cases.

RANK_REASON Cluster includes a quantized version of a frontier model released by a major hardware vendor (Nvidia) and its original developer (DeepSeek AI), alongside a community-driven uncensored variant.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

Nvidia releases quantized DeepSeek-V4.1-Flash-1017; uncensored version also emerges

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1 / 100
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Frontier Release
Cluster includes a quantized version of a frontier model released by a major hardware vendor (Nvidia) and its original developer (DeepSeek AI), alongside a community-driven uncensored variant.
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3 independent sources
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model release, product
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High
Clearly on-topic for AI-industry coverage.
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3 days old
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COVERAGE [3]

  1. Hugging Face Trending Models TIER_1 Nederlands(NL) · nvidia ·

    nvidia/DeepSeek-V4.1-Flash-1017-NVFP4

    image-text-to-text · 1,473 downloads · 106 likes

  2. dev.to — LLM tag TIER_1 English(EN) · NovaAPI ·

    DeepSeek V4.1 Flash 1017: what actually changed

    <p>DeepSeek shipped V4.1 Flash 1017 on 17 October. The interesting part is not the benchmark chart — it is the output length.</p> <p>Shorter outputs are the quietest cost lever in a coding-agent workload. An agent that produces the same diff in fewer tokens costs less per task wi…

  3. r/LocalLLaMA TIER_1 English(EN) · /u/gladkos ·

    Running UNCENSORED DeepSeek-V4.1-Flash-1017 on a 12 Gb VRAM

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1xm0uy0/running_uncensored_deepseekv41flash1017_on_a_12/"> <img alt="Running UNCENSORED DeepSeek-V4.1-Flash-1017 on a 12 Gb VRAM" src="https://external-preview.redd.it/dFlp54iSI2fuAJd0F74XniA6CvPYkJawTSjOGnMFg…

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