⚡ LLM Optimization - jimman

Google DeepMind releases Gemma 4 QAT, but Unsloth developer Daniel Han warns naive llama.cpp conversions suffer accuracy loss

⚡Model Efficiency News

digg.com·

[AINews] Open Models, Model Labs vs Agent Labs, and What's Untrainable — Sarah Guo

⚡Model Efficiency News

latent.space

BeeLlama.cpp DFlash on Strix Halo: 2.7x Gemma 31B, But MTP Is Still Faster

⚡Model Efficiency

sleepingrobots.com·

Here's a llama.cpp CLI Command builder.

⚡Model Efficiency

llamabuilding.com··r/LocalLLaMA

Holding the FP8 Quality Ceiling at 8-Bit Weights and Activations: INT8 and GGUF Post-Training Quantization of Ideogram 4.0 for Consumer GPUs

⚡Model Efficiency Academic

arxiv.org·

Valkey: Unlocked Seattle: The Best Systems Let You Sleep At Night

⚡Model Efficiency Blog

valkey.io·

A system programmer’s guide to LLM inference

⚡Model Efficiency Blog

blog.xiangpeng.systems··Hacker News

From GPU to Token: The 8-Layer Observability Stack for AI Infrastructure

⚡Model Efficiency Blog

jimmysong.io·

High-end Hitachi Vantara arrays and Nvidia AI support

⚡Model Efficiency News

blocksandfiles.com·

AMD's Lemonade SDK For Local AI Adds NVIDIA CUDA Support

⚡Model Efficiency

phoronix.com··r/artificial

Ollama 0.30 delivers faster NVIDIA GPU performance and wider hardware support

⚡Model Efficiency

alternativeto.net·

CommBench: Can LLMs Write Correct and Efficient GPU Communication Code?

🔓Open Source

uccl-project.github.io··Hacker News

Ideogram4 GGUF is out!

✍️Prompt Engineering

huggingface.co··r/StableDiffusion

Token4Token — pay-per-token inference on Gnosis + Swarm

⚡Model Efficiency

t4t.eth.link··Hacker News

Anthropic's most powerful model comes with a kill switch aimed at you

🚀Entertainment

boingboing.net·

Gemma 4 12B: A unified, encoder-free multimodal model

⚡Model Efficiency Discussion

news.ycombinator.com··Hacker News

libertywing/FlashMemory-Deepseek-V4: FlashMemory DS-V4 Retriever: a lightweight retriever that sparsifies DeepSeek-V4 CSA KV-cache. Weights available on Hugging Face.

⚡Model Efficiency Code

github.com·

Google Shrank Gemma 4 by 72% and Unsloth Fixed the 4-Bit Bug Nobody Else Caught on One 4090, and 4-Bit Shouldn’t Be This Good

🤖AI Blog

towardsai.net·

6. Air-Gapped Claude Code - The Claude Code SRE Handbook

Report: GKE Inference Gateway delivers up to 92% faster AI responses

Google DeepMind releases Gemma 4 QAT, but Unsloth developer Daniel Han warns naive llama.cpp conversions suffer accuracy loss

[AINews] Open Models, Model Labs vs Agent Labs, and What's Untrainable — Sarah Guo

BeeLlama.cpp DFlash on Strix Halo: 2.7x Gemma 31B, But MTP Is Still Faster

Here's a llama.cpp CLI Command builder.

Holding the FP8 Quality Ceiling at 8-Bit Weights and Activations: INT8 and GGUF Post-Training Quantization of Ideogram 4.0 for Consumer GPUs

Valkey: Unlocked Seattle: The Best Systems Let You Sleep At Night

A system programmer’s guide to LLM inference

From GPU to Token: The 8-Layer Observability Stack for AI Infrastructure

High-end Hitachi Vantara arrays and Nvidia AI support

AMD's Lemonade SDK For Local AI Adds NVIDIA CUDA Support

Ollama 0.30 delivers faster NVIDIA GPU performance and wider hardware support

CommBench: Can LLMs Write Correct and Efficient GPU Communication Code?

Ideogram4 GGUF is out!

Token4Token — pay-per-token inference on Gnosis + Swarm

Anthropic's most powerful model comes with a kill switch aimed at you

Gemma 4 12B: A unified, encoder-free multimodal model

libertywing/FlashMemory-Deepseek-V4: FlashMemory DS-V4 Retriever: a lightweight retriever that sparsifies DeepSeek-V4 CSA KV-cache. Weights available on Hugging Face.

Google Shrank Gemma 4 by 72% and Unsloth Fixed the 4-Bit Bug Nobody Else Caught on One 4090, and 4-Bit Shouldn’t Be This Good