Quantization explained: how big AI models run on small hardware
Quantization shrinks AI models by storing weights with fewer bits. How 8-bit and 4-bit formats work, GGUF, GPTQ and AWQ, and the quality trade-offs to expect.
AI Desk3 min read
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Step-by-step AI guides and tutorials for beginners, power users and developers.
Quantization shrinks AI models by storing weights with fewer bits. How 8-bit and 4-bit formats work, GGUF, GPTQ and AWQ, and the quality trade-offs to expect.
AI Desk3 min read
What happens when a server answers thousands of LLM requests: prefill and decode, the KV cache, continuous batching, PagedAttention and the metrics that matter.
AI Desk3 min read
Estimate the GPU memory needed to run or fine-tune a language model: weights, KV cache, activations and overhead, with worked examples for 8B and 70B models.
AI Desk4 min read
The most important tool in AI engineering: how to collect test cases, define success criteria, score outputs automatically and by hand, and run evals on every change.
AI Desk3 min read