Inference

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DiffusionGemma: 4x Faster Text Generation

 🧠LLMs  Content type: News  Content type: Blog

heterodoxin/graphkv: Graph-guided KV cache compression for memory-efficient LLM inference.

 🧠LLMs  Content type: Code
github.com··r/LocalLLaMA

MiMo-v2.5-Pro-UltraSpeed: 1T model with 1000 TPS

 🎛️Fine-tuning  Content type: Blog

google/gemma-4-31B-it · fix: chat template — null handling, reasoning preservation, turn-tag balance, input validation

 🧠LLMs

Pruned YOLOv8 ONNX INT8 Fails: 3 Fixes That Work

 🎛️Fine-tuning  Content type: Blog  Content type: Discussion
tildalice.io·

China's Xiaomi MiMo Is Now 15X Faster Than ChatGPT and Claude (4 minute read)

 🌐Open Source AI  Content type: News
decrypt.co·

MLPerf and the rise of latency-aware LLM benchmarking

 🧠LLMs
edn.com·

TFLite Edge Model Quantizer Snippet

 🧠LLMs

KaiFelixBennett/gemma4-turboquant-rdna4: Run Gemma-4-31B at full 256K context on a $1,400 AMD RDNA4 GPU (gfx1201): TurboQuant KV cache + HIP-graph-safe Flash-Attention for llama.cpp, fully measured on real hardware.

 🎛️Fine-tuning  Content type: Code
github.com··Hacker News

Running Qwen 35B MoE at 450k Context on a Single 32GB GPU

 🧠LLMs

UniSVQ: 2-bit Unified Scalar-Vector Quantization

 🎛️Fine-tuning  Content type: Academic
arxiv.org·

On-device AI is a margin decision

 🌐Open Source AI  Content type: Blog
ziraph.com··Hacker News

Youssof Altoukhi (@Youssofal_)

 🧠LLMs
xcancel.com··r/LocalLLaMA

The latest Gemma 4 models use a training trick to slash their on-device memory footprint

 🌐Open Source AI
androidauthority.com·

Show HN: Ext-Infer

 🧠LLMs

What's in the Box? A Field Guide to AI Models

 🌐Open Source AI  Content type: Blog
iankduncan.com·

OpenCV 5.0 Computer Vision Library Released with Rewritten DNN Engine

 🌐Open Source AI
linuxiac.com·

A field journal on Ray Data and Daft for multimodal data lake (14 minute read)

 🧠LLMs  Content type: Blog
mehulbatra.medium.com·

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

 🌐Open Source AI
phoronix.com·

huawei-csl/KVarN: KVarN is a native vLLM KV-cache quantization backend for your agents: 3-5x more context, throughput above FP16, and FP16-level accuracy. Calibration-free, one flag.

 🧠LLMs  Content type: Code
github.com··Hacker News
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