Inference Engineering

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AMD Radeon RX 9070 GRE vs. Radeon RX 9070

 💰Compute Costs
club386.com·

Apples to Apples: MLX vs. Llama.cpp for Gemma 4 12B on an M1 16GB

 💰Compute Costs  Content type: Blog
ziraph.com··Hacker News
Less-relevant results

Token4Tokenpay-per-token inference on Gnosis + Swarm

 🗄️KV Cache
t4t.eth.link··Hacker News

Why I care so much about energy per token

 💰AI Economics  Content type: Blog
ziraph.com··Hacker News

The Memory Problem is Solved: How Google’s Memory Caching Makes RNNs Smart Again

 🎯Fine-tuning  Content type: Blog
medium.com·

1-bit and 1.58 bit LLM Benchmarking on Jetson Orin Nano Super | Bonsai LM

 🗄️KV Cache
smolhub.com··r/LocalLLaMA

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

 🗄️KV Cache
sleepingrobots.com·

NetX-lab/Frontier: Frontier: A Discrete-Event Simulator for Modern LLM Serving

 🗄️KV Cache  Content type: Code
github.com··Hacker News

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

 🗄️KV Cache  Content type: Blog
towardsai.net·

Two Leaps to 1000 Tokens/s on a 1T-Parameter Model: On Inference Systems, Execution Boundaries, and Co-Design

 🗄️KV Cache  Content type: Blog
tilert.ai··Hacker News

Benchmarking dots.tts on Strix Halo

 ♟️Game Theory
sleepingrobots.com·

STAR-KV: Low-Rank KV Cache Compression via Soft Thresholding for Adaptive Rank Control

 🗄️KV Cache  Content type: Academic
arxiv.org·

A system programmer’s guide to LLM inference

 💰Compute Costs  Content type: Blog

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

 🔍RAG  Content type: Blog

MLPerf and the rise of latency-aware LLM benchmarking

 🤖AI
edn.com·

A UK startup says it can cut data centre network power by 81% by replacing every electrical switch with light

 💰AI Economics  Content type: News
thenextweb.com·

AI Serving Platform That Adapts to Your Model

 🗄️KV Cache  Content type: Blog
databricks.com·

Build a local voice agent with Red Hat OpenShift AI

 🗄️KV Cache
developers.redhat.com·

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.

 🗄️KV Cache  Content type: Code
github.com··Hacker News

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

 🗄️KV Cache  Content type: Academic
arxiv.org·
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