AI Models
Model releases, benchmarks, inference and fine-tuning.
AI Model Local Deployment in Practice: Benchmarking Grug-35B-v2 MLX 4-bit on an M4 Max
A single-machine scorecard for the text-only Qwen3.5-MoE pack pgmharikrishnan/grug-35b-v2-MLX-4bit under mlx-serve v26.10.2 — quality, throughput, memory, and one honest gap.
AI Model Local Deployment, Explained: What mlx-serve Adds on Top of MLX
A technical explainer on mlx-serve as a local inference server for MLX-compatible models — why the serving layer is a separate thing from MLX, what it exposes, and how to deploy AI model weights you already have.
Active Parameters in AI Model Local Deployment: A Decode/Prefill and Quality Head-to-Head
A head-to-head look at cohort-relative speed and quality indices in an October 2026 local model benchmark.
How We Benchmark AI Model Local Deployment: Building a Repeatable Local-Model Suite
A local-model benchmark suite under development separates model quality, throughput, latency, and context behaviour, fixes the protocol and setup for repeatability, retains per-run evidence, and refuses to collapse unlike dimensions into a composite winner or a general recommendation.
Apple MLX for AI Model Local Deployment: Unified Memory Explained
A practical guide to MLX, unified memory, and the difference between model capacity and inference performance.
A Mixed-Precision LFM2.5 Pack Edges the Stock 4-Bit Model—With Important Caveats
A comprehensive analysis comparing the stock LiquidAI 4-bit model pack against a custom mixed-precision MLX build, covering benchmark results, deployment strategies, and agentic AI integration.
When ‘Plain’ Wins: Model Trade-offs Across AI Model Local Deployment Benchmarks
Expanded article analyzing cross-model plain vs best cell comparisons for local LLM deployment with complete setup, data table, explanations, and disclaimer.
AI Model Local Deployment Architecture: How Five 2026 Open Weights Stack Up Under the Hood
A technical breakdown of MoE vs dense design choices, context window engineering, and benchmark positioning across Flash Next, Qwen3.8 27B, Muse Glimmer 30B, MiniCPM-V 4.7, and LFM2.5-24B-A2B.
AI Model Local Deployment in 2026: A Cohort Leaderboard From MiniCPM to LFM2.5
Five open-weight models dropped within hours of each other in late October 2026 — MiniCPM-V 4.7, Muse Glimmer 30B, Qwen3.8-27B, Flash Next, and LFM2.5-24B-A2B. Here's what each one brings to local inference and how to pick between them.
Anthropic's Three-Tier Cyber Access: A Blueprint for AI Cloud Infrastructure Companies in India
Anthropic folded Project Glasswing and its Cyber Verification Program into a single tiered access framework for Claude's most capable models. The design is a useful study in access governance for any company building on frontier AI.
PoeLLM and AI Driven Endpoint Security Trends Nobody Planned For
Lumen Black Lotus Labs discovered PoeLLM, a malware campaign compromising over 3,400 exposed AI servers for cryptomining and exploit propagation using GitHub-hosted poetry for C2.
The AI Impact on Human Psychology Is Written in Six Decades of Pop Lyrics
A Queen Mary University of London study ran AI language models over 380,000 songs from 1960 to 2023 and found virtues fading while vices and negativity climb. Here's what it reveals — and what it can't.