Q4_K_M hits quantization sweet spot

Q4_K_M is the de facto standard for local inference because it minimizes perplexity loss without the VRAM overhead of 6-bit or 8-bit models.

• –Mixed-precision approach keeps critical attention and feed-forward layers at 6-bit while most weights stay at 4-bit.
• –Significantly outperforms legacy Q4_0 and Q4_1 formats, providing "4-bit speeds" with "near 6-bit intelligence."
• –Ideal for 8B models on 8GB VRAM GPUs, making high-quality local AI accessible on standard laptops.
• –Widely adopted as the default "latest" tag in Ollama and LM Studio, simplifying deployment for developers.