Weekly tutorials and news on adapting large language models (LLMs) to your tasks and hardware using the most recent techniques and models. The Kaitchup proposes a collection of 180+ AI notebooks regularly updated.
| Platform |  | Pricing | Freemium | Publishes | Twice weekly |
|---|---|---|---|---|---|
| Issues | 479 | Founded | 3 years ago | Last Issue | 7 days ago |
| Active | |||||
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kaitchup.substack.comLatest Issues
Qwen3.8 27B Quantization: NVFP4, INT4, GSQ 3-bit, INT3/INT2, and Escha-W2 Compared
9 quantized Qwen3.8 27B models tested for accuracy, token efficiency, reasoning behavior, MTP, and VRAM usage
The available Qwen3.8 27B quantizations cover a wide range of formats and data types: mixed 2-bit/3-bit, INT3, mixed INT3/INT4/IN...
DeepSeek V4.1 Flash: 552B Parameters, Lower Inference Costs
Hi everyone,
DeepSeek released V4.1 Flash this week. Despite the name, this is much more than another refresh of V4 Flash: DeepSeek changed the architecture itself, with a strong focus on what is increasingly becoming the expensive part of...
Qwen3.8 27B for Long-Horizon Agentic Coding: Pi vs Claude Code vs Mini-SWE
Accuracy, token efficiency, reasoning effort, preserved thinking, and agent-harness ablations across 113 long-horizon coding tasks
Qwen3.8 27B is one of the strongest open-weight models I’ve tested, while still fitting on a single GPU.
Muse Glimmer Quantization Review: INT4, NVFP4 & 3.5-Bit Compared
20,000+ prompts for accuracy, token efficiency, reasoning behavior, and VRAM usage
Muse Glimmer’s release a few weeks ago was an unexpected piece of good news from Meta, although the impressive Qwen3.8 27B quickly outperformed it.
The Era of Agentic Benchmaxxing
Hi everyone,
This was a particularly interesting week, with major model releases from Meta (Muse Spark 1.3), Google (Gemini 3.8 Flash), OpenAI (GPT-6), and Anthropic (Fable 5.1).
But if we looked only at the published benchmarks, we might...
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Research scientist in NLP/AI.
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