--- title: Unsloth Dynamic 2.0 GGUFs | daily.dev description: Unsloth Dynamic 2.0 GGUFs introduces major upgrades to dynamic quantization for large language models. Key improvements include use of KL divergence for better... canonical: https://daily.dev/posts/unsloth-dynamic-2-0-ggufs-pggi40vtt twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Unsloth Dynamic 2.0 GGUFs | daily.dev og:description: Unsloth Dynamic 2.0 GGUFs introduces major upgrades to dynamic quantization for large language models. Key improvements include use of KL divergence for better... og:url: https://daily.dev/posts/unsloth-dynamic-2-0-ggufs-pggi40vtt og:image: https://api.daily.dev/og/posts/Pggi40VtT.png og:image:alt: Unsloth Dynamic 2.0 GGUFs og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Unsloth Dynamic 2.0 GGUFs **[Hacker News](https://daily.dev/sources/hn)** · 1 min read · 2 upvotes · 0 comments ## Summary Unsloth Dynamic 2.0 GGUFs introduces major upgrades to dynamic quantization for large language models. Key improvements include use of KL divergence for better quantization quality, analysis of calibration dataset overfitting risks, MMLU benchmark replication, Gemma 3 QAT replication with benchmarks, and bug fixes plus run instructions for Llama 4 Scout. Step-by-step commands are provided for building llama.cpp with CUDA support and running the Llama 4 Scout 17B model using IQ2_XXS quantization with mixed CPU/GPU offloading. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [LFM2.5 Q4\_0 Checkpoints from Quantization-Aware Distillation](https://daily.dev/posts/lfm2-5-q4-0-checkpoints-from-quantization-aware-distillation-qyvxdigkf) · Hugging Face · 1 upvotes · 0 comments - [LLM quantization guide: How to do it, and how it helps](https://daily.dev/posts/llm-quantization-guide-how-to-do-it-and-how-it-helps-ibtxb1uok) · Red Hat Developer · 0 upvotes · 0 comments - [Quantizing LLMs Step-by-Step: Converting FP16 Models to GGUF](https://daily.dev/posts/quantizing-llms-step-by-step-converting-fp16-models-to-gguf-lqamqetgk) · Machine Learning Mastery · 2 upvotes · 0 comments - [Quantization Explained: Run 70B Models on Consumer GPUs](https://daily.dev/posts/quantization-explained-run-70b-models-on-consumer-gpus-2lmh0n2hc) · SitePoint · 0 upvotes · 0 comments --- Tags: [#data-science](https://daily.dev/tags/data-science), [#llama-cpp](https://daily.dev/tags/llama-cpp), [#llm](https://daily.dev/tags/llm), [#local-ai](https://daily.dev/tags/local-ai), [#unsloth](https://daily.dev/tags/unsloth) [View this post on daily.dev](https://daily.dev/posts/unsloth-dynamic-2-0-ggufs-pggi40vtt) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Unsloth Dynamic 2.0 GGUFs","url":"https://daily.dev/posts/unsloth-dynamic-2-0-ggufs-pggi40vtt","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/unsloth-dynamic-2-0-ggufs-pggi40vtt"},"datePublished":"2026-02-28T13:13:25.422Z","dateModified":"2026-10-15T02:24:29.645Z","description":"Unsloth Dynamic 2.0 GGUFs introduces major upgrades to dynamic quantization for large language models. 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