NVIDIA drops AITune – auto-selects fastest inference backend for PyTorch models

<!-- SC_OFF --><div class="md"><p>The modern ML (LLM) compiler stack is brutal. TVM is 500K+ lines of C++. PyTorch piles Dynamo, Inductor, and Triton on top of each other. I built

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1si7xzy/spectralai_a_project_to_use_nvidia_rt_cores_to/"> <img alt="Spectral-AI - a project to use Nvidia RT

<!-- SC_OFF --><div class="md"><p>After burning way too much money on GPT-4 API calls, I finally went all-in on local models with Ollama. The progress in 2026 is insane

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1x5t1tm/nvidia_nemotron_bolt_35_74b_a9b_releases_oct_15th/"> <img alt="NVIDIA Nemotron Bolt 3.5 74B A9B

<!-- SC_OFF --><div class="md"><p>Enterprises running always-on AI agents keep hitting the same tradeoff. Send every task to a frontier model and the bill climbs fast. Build

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s59rct/rys_part_3_llms_think_in_geometry_not_language/"> <img alt="RYS Part 3: LLMs think in geometry, not