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4 articles found per "llama-cpp"
Yzma: embeddings up to 2.6x faster than Ollama, the comparison
Yzma calls llama.cpp in the same process: no server, no round trip. It is 2.6x faster than Ollama on embeddings — with the numbers, the math and the setup.
A Model Without a GPU: When the CPU Is Actually Enough
In 2026, CPU-only inference is no longer a fallback: when it genuinely works, what speed to expect, and which levers to pull to squeeze the most out of your processor.
KV cache: why your RAM needs more than just the model
What the KV cache is, the formula to calculate it with real numbers from Llama 3.1 8B and Qwen3 8B, and the three levers to manage it: context, quantization and flash attention.
GGUF: The Format That Keeps Models on Your Hardware
GGUF is the single-file format that ships models for local inference: a header with a signature and version, key-value metadata, a tensor index, and weights aligned for fast mmap loading. Quantization types with real sizes (8B from 14.96 GiB at F16 to 4.58 GiB at Q4_K_M), the filename convention, and the rule for picking a size against your VRAM or RAM.