Shapelearn Qwen 3.8 27B (13.1 GB VRAM)
(news.ycombinator.com)
1.
2.
Getting 50 GB/S Back from the Apple Neural Engine
(news.ycombinator.com)
3.
Georgi Gerganov on llama.cpp/ggml future after Nvidia acquisition of HuggingFace
(news.ycombinator.com)
4.
A practical guide to running 8x RTX PRO 6000's
(news.ycombinator.com)
5.
Run Qwen3.8 27B locally: real numbers from my Mac Studio
(news.ycombinator.com)
6.
AI Engineer Notebooks – free, framework-free RAG/agents/evals on Colab
(news.ycombinator.com)
7.
Kids outlearn AI—and we still don’t know why
(technologyreview.com)
8.
Vomit: Clean up Claude 5's token output with a separate LLM
(news.ycombinator.com)
9.
Clean up Claude 5's token vomit with a separate LLM
(news.ycombinator.com)
10.
DFlash 2: Keep Drafting Parallel
(news.ycombinator.com)
11.
Unsloth Dynamic 3.0 GGUFs
(news.ycombinator.com)
12.
Show HN: Shoehorn – Quantize any model down to run on your machine
(news.ycombinator.com)
13.
Llama.cpp v0.1.0
(news.ycombinator.com)
14.
Qwen3.8-27B at 256K on a 24GB RTX PRO 4000 SFF (432 GB/s): 50 tok/s with MTP
(news.ycombinator.com)
15.
llama.cpp
(news.ycombinator.com)
16.
Apple Silicon and macOS VMs: Faster LLM Inference with llama.cpp
(news.ycombinator.com)
17.
Apple Silicon and macOS VMs: 11–16× Faster LLM Inference with Llama.cpp
(news.ycombinator.com)
18.
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Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows
(news.ycombinator.com)
22.
Meta Muse Glimmer – Open weights 30B local coding model
(news.ycombinator.com)
23.
Meta Muse Glimmer – open weights 30B local coding model
(news.ycombinator.com)
24.
Building a Rust Inference Engine That Matches Llama.cpp
(news.ycombinator.com)
25.
Homebench – Benchmark local LLMs for speed, memory, and quality
(news.ycombinator.com)
26.
AirLLM 70B inference with single 4GB GPU
(news.ycombinator.com)
27.
Petals: Run LLMs at home, BitTorrent-style
(news.ycombinator.com)
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30.
Same model, same Q4_K_M label: 5.02, 5.07 and 5.27 bits per weight
(news.ycombinator.com)
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