LLM Quantization Explained: GGUF vs GPTQ vs AWQ (2026 Guide)
Clear explanation of GGUF, GPTQ, and AWQ quantization for local LLMs. Which format to use with Ollama, llama.cpp, and vLLM, and how much quality you actually lose at each level.
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#GPUFound 8 posts with this tag
RTX 5090 vs RTX 4090 for Deep Learning: Is the Upgrade Worth It?
RTX 5090 vs RTX 4090 benchmarks for AI and deep learning. VRAM, memory bandwidth, training speed, and whether the upgrade makes financial sense in 2026.
Fix CUDA Out of Memory in PyTorch: 10 Proven Solutions
The complete guide to diagnosing and fixing the dreaded 'RuntimeError: CUDA out of memory' in PyTorch. Covers batch size, mixed precision, gradient checkpointing, and more.
How Much VRAM for FLUX Image Generation? Complete Guide
Exact VRAM requirements for FLUX.1 Dev, Schnell, and Pro models. Benchmarks across RTX 3060, 4090, and 5090 with quantization options for every GPU budget.
Best GPU for Running Llama 4 Locally: Scout & Maverick Hardware Guide
Complete hardware requirements for running Meta's Llama 4 Scout (109B) and Maverick (400B) locally. VRAM requirements, quantization options, and GPU recommendations for every budget.
Building an AI Workstation (2026)
Step-by-step guide for assembling the perfect development rig for AI, ML, and Deep Learning workloads in 2026. Updated GPU, RAM, and storage recommendations.
Best DL Frameworks for 2025: PyTorch vs TensorFlow vs JAX Benchmarked
Compare PyTorch, TensorFlow, and JAX for GPU training in 2025: performance benchmarks, VRAM efficiency, deployment, and which framework fits your workload, from LLM training to production inference.
Best GPUs for Deep Learning in 2025: RTX 5090, A100, H100 Compared
Compare the best GPUs for deep learning in 2025: RTX 5090, A100, H100, and AMD alternatives. VRAM requirements, CUDA vs ROCm, and cloud vs local hardware. Everything you need to choose the right GPU for PyTorch, TensorFlow, and JAX.
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