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Tuning the Steam Deck OLED Kernel for Gaming Performance

Tuning the Steam Deck OLED Kernel for Gaming Performance

Steam Deck OLED tuning is no longer just about pushing sliders and hoping for more FPS. The stack is layered. Valve’s kernel, your Proton version, the game engine, and power policy all interact. Tune one layer alone and you often trade smoothness for crashes, or frame rate for battery drain.

This guide chases one goal: steadier frame times and longer battery life, without turning your Deck into a fragile science project. You get a safe workflow, specific kernel options, and game profiles you can reuse.

High-end gaming desktop with illuminated NVIDIA GPU visible through a glass side panel, surrounded by floating holographic neural network diagrams and data streams

Run Llama 4 Scout Locally: 24GB VRAM, GGUF, Real Speeds

You can run Llama 4 Scout on a 24 GB consumer GPU, but only with an aggressive quantization and some patience. Scout is a 109B-parameter Mixture-of-Experts model, and even its smallest Unsloth dynamic GGUF build is about 32 GB, so a 24 GB card runs it with CPU offload at roughly 20 tokens per second. This guide covers which Llama 4 model fits your hardware, the real VRAM math, and the fastest way to get it running.

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Gemma 4 vs Qwen 3.5 vs Llama 4: Which Open Model Should You Actually Use? (2026)

Gemma 4 vs Qwen 3.5 vs Llama 4: Which Open Model Should You Actually Use? (2026)

Gemma 4, Qwen 3.5, and Llama 4 compared on benchmarks, licensing, speed, and hardware so you can pick the right open model fast.

5 Open Source Repos That Make Claude Code Unstoppable

5 Open Source Repos That Make Claude Code Unstoppable

Five March 2026 repos extend Claude Code with autonomous ML, self-healing skills, GUI automation, multi-agent coordination, and Google Workspace access.

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DeepSeek V4 Tech Report: 3 Tricks That Cut Compute 73%

DeepSeek V4 ships 1.6T parameters and 1M context using only 27% of V3.2's inference FLOPs. Inside the hybrid attention, mHC residuals, and Muon optimizer.

Cracked stone tablet engraved with a bulleted system prompt, four crossed-out goblin silhouettes repeated, a tiny goblin escaping with upvote-arrow sparks, a giant dollar-sign price tag, and figures refusing to step onto a glossier pedestal.

GPT 5.5 Reddit Reception: Goblins and the Cost Backlash

GPT-5.5 Reddit reception: viral goblin prompt leak, doubled pricing backlash, and 5.4 holdouts citing hallucination regressions in factual recall workflows.

What X and Reddit Users Are Saying about Claude Opus 4.7

What X and Reddit Users Are Saying about Claude Opus 4.7

How power users on X and Reddit reacted to Claude Opus 4.7: praise for agentic coding, token burn concerns, and teams' practical prompting habits.

Qwen3.6-35B-A3B: Alibaba's Open-Weight Coding MoE

Qwen3.6-35B-A3B: Alibaba's Open-Weight Coding MoE

Alibaba's sparse Mixture-of-Experts: 35B total parameters, 3B active per token. Q4 quantization runs on MacBook Pro M5, matches Claude Sonnet performance.

Alacritty vs. Kitty: Best High-Performance Linux Terminal

Alacritty vs. Kitty: Best High-Performance Linux Terminal

Alacritty vs Kitty in 2026: emoji and Unicode rendering, real benchmarks, latency, memory, maintainer reputation, and the right terminal for your workflow.

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