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1.
Benchmarking Pocket-Scale Inference (news.ycombinator.com)
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Why your local LLM feels dumber than it is (news.ycombinator.com)
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Show HN: Shoehorn – Quantize any model down to run on your machine (news.ycombinator.com)
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Qwen 3.8 27B (news.ycombinator.com)
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Qwen 3.8 27B is out: open weights, best local dense model yet (news.ycombinator.com)
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Compression is prediction (news.ycombinator.com)
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Compression Is Prediction (news.ycombinator.com)
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Show HN: Cactus Hybrid: We taught Gemma 4 to know when it's wrong (news.ycombinator.com)
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The 4-Bitter Lesson: Balancing Stability and Performance in NVFP4 RL (news.ycombinator.com)
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Asymmetric Quantization: Near-Lossless Retrieval with 97% Storage Reduction (news.ycombinator.com)
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Integer Quantization: Deep Dive (news.ycombinator.com)
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KVarN: Native vLLM KV-cache quantization back end by Huawei (news.ycombinator.com)
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Show HN: I successfully failed at one-shot-ing a video codec like h.264 (news.ycombinator.com)
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Google unveils TurboQuant, a new AI memory compression algorithm — and yes, the internet is calling it ‘Pied Piper’ (techcrunch.com)
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Google's TurboQuant AI-compression algorithm can reduce LLM memory usage by 6x (arstechnica.com)
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Google says new TurboQuant compression can lower AI memory usage without sacrificing quality (arstechnica.com)
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Quantization from the Ground Up (news.ycombinator.com)
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TurboQuant: Redefining AI efficiency with extreme compression (news.ycombinator.com)
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