🚀 Inference - abhik

🧠LLMs Code

github.com··Hacker News

Using local LLMs for agentic coding

🧠LLMs Blog

blog.alexewerlof.com·

RKSC: Reasoning-Aware KV Cache Sharing and Confident Early Exit for Multi-Step LLM Inference

🧠LLMs Academic

arxiv.org·

How to Run Gemma 4 12B Locally - The Best AI For Consumer Laptops

🤖AI Engineering Video

youtube.com·

not much happened today | AINews

🤖AI Engineering

news.smol.ai·

Youssof Altoukhi (@Youssofal_)

🤖AI Engineering

xcancel.com··r/LocalLLaMA

Beyond Per-Token Pricing: A Concurrency-Aware Methodology for LLM Infrastructure Cost Estimation

🤖AI Engineering Academic

arxiv.org·

The Death of the Four Golden Signals: Designing Telemetry for Non-Deterministic Infrastructure

🛡️Reliability Engineering

devops.com·

RightNow-AI/AutoMegaKernel: An agent harness that compiles a model into one provably-correct, self-retargeting CUDA megakernel and self-tunes it past cuBLAS at batch-1 LLM decode.

🧠LLMs Code

github.com··Hacker News

Introducing Granite Libraries and Project Granite Switch

🤖AI Engineering Blog

research.ibm.com··Hacker News

3x Faster Search: Parallel Test-Time Scaling with Instructed-Retriever-1

🤖AI Engineering Blog

databricks.com·

[eCHO News] Episode #104: mTLS for Cilium. Lisp for eBPF

🔬eBPF

isovalent-9197153.hs-sites.com·

Fine-tuning Multi-modal LLMs with ART: Art-based Reinforcement Training

🧠LLMs Academic

arxiv.org·

bigattichouse/packed-twin-inference: PTI achieves ~2× throughput using a single quantized model (Q5_K_M or better) by running 4 generation streams in one batched decode call. The GPU loads model weights once per step and produces 4 predictions simultaneously. KV cache overhead is ~0.8 GiB total for all 4 streams. No draft model. No quality loss

🧠LLMs Code

github.com··r/LocalLLaMA

google/gemma-4-12B-it-qat-q4_0-gguf

🧠LLMs

huggingface.co·

APEX4: Efficient Pure W4A4 LLM Inference via Intra-SM Compute Rebalancing

🧠LLMs Academic

arxiv.org·

not much happened today | AINews

🤖AI Engineering

news.smol.ai·

Nvidia DGX Spark GB10 – AI Models and Guide with vLLM and Autonomous Script

🧠LLMs Code

github.com··Hacker News

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

What Arm-based innovations happened in May 2026?

defai-digital/ax-engine: Apple Silicon LLM runtime supporting Gemma 4 and Qwen 3.6 MTP modes

Using local LLMs for agentic coding

RKSC: Reasoning-Aware KV Cache Sharing and Confident Early Exit for Multi-Step LLM Inference

How to Run Gemma 4 12B Locally - The Best AI For Consumer Laptops

not much happened today | AINews

Youssof Altoukhi (@Youssofal_)

Beyond Per-Token Pricing: A Concurrency-Aware Methodology for LLM Infrastructure Cost Estimation

The Death of the Four Golden Signals: Designing Telemetry for Non-Deterministic Infrastructure

RightNow-AI/AutoMegaKernel: An agent harness that compiles a model into one provably-correct, self-retargeting CUDA megakernel and self-tunes it past cuBLAS at batch-1 LLM decode.

Introducing Granite Libraries and Project Granite Switch

3x Faster Search: Parallel Test-Time Scaling with Instructed-Retriever-1

[eCHO News] Episode #104: mTLS for Cilium. Lisp for eBPF

Fine-tuning Multi-modal LLMs with ART: Art-based Reinforcement Training

google/gemma-4-12B-it-qat-q4_0-gguf

APEX4: Efficient Pure W4A4 LLM Inference via Intra-SM Compute Rebalancing

not much happened today | AINews

Nvidia DGX Spark GB10 – AI Models and Guide with vLLM and Autonomous Script