RTX 5090 Benchmark: Flux.2 Dev Performance in FP8 and GGUF
Local AI inference performance is traditionally evaluated through a binary metric: whether a model fits entirely within physical VRAM. In…
Author: Jérôme Lafont
Consultant and senior developer specialized in AI and information systems, with extensive experience in the software industry. Over the years, I’ve contributed to large-scale enterprise solutions, open-source projects, and consumer software, always driven by innovation and practical impact. Find me on LinkedIn
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Reliability and Contextual Drift: Why LLMs Lose Track in Long Contexts
The evolution of Large Language Models (LLMs) in 2026 is defined by an aggressive race toward ever-larger context windows. With…
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Fish Audio S2 Pro: How to Use a Voice Reference for High-Fidelity Voice Cloning
Fish Audio S2 Pro represents the state-of-the-art in multilingual text-to-speech, leveraging an asymmetric Dual-Autoregressive (Dual-AR) architecture—combining a 4B parameter Slow AR model…
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Beyond semantic search: Architecting the multi-vector RAG stack in 2026
In the early days of the generative AI boom, semantic search was hailed as the definitive solution for knowledge retrieval….
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The Architectural Ceiling: Why Gemini 3.1 Pro and Claude 4.6 Opus Diverge on Output Length
In 2026’s high-stakes Large Language Model landscape, a structural divergence has become a primary friction point for power users: the “Output…
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The illusion of the trust layer: securing LLM prompts through interception
The rapid integration of Large Language Models (LLMs) into the corporate workflow has birthed a significant security paradox: how can…
