Skip to main content
株式会社オブライト

Articles tagged "量子化"

4 articles

AI2026-08-20
Unsloth Dynamic 3.0 GGUF Quantization Explained
Unsloth Dynamic 3.0 is a GGUF quant method with fresh imatrix data, up to 10% higher accuracy at same size vs 2.0. Sizes, VRAM, setup. Updated Aug 2026.
GGUF量子化ローカルLLM
AI2026-08-13
Local LLM Inference Engines Compared — llama.cpp, Ollama, vLLM, LM Studio, MLX, TensorRT-LLM
Comparing local LLM engines: Ollama and llama.cpp solo, MLX on Apple Silicon, vLLM for concurrent serving, TensorRT-LLM for NVIDIA, LM Studio for GUI trials.
ローカルLLMローカルAIOllama
AI2026-07-24
GGUF Quantization: Which Level to Pick (Q4_K_M, Q5_K_M, Q8_0, IQ) for Local LLMs
Start with Q4_K_M; step up to Q5_K_M or Q6_K if you have VRAM headroom. This guide explains GGUF naming, the quality/speed/VRAM tradeoffs per level, IQ (imatrix) quants, and how to choose by task. Updated July 2026.
GGUF量子化ローカルLLM
AI2026-07-15
PrismML Bonsai 27B Explained: Ternary and 1-Bit Builds of Qwen3.6-27B That Put a 27B-Class Model on an iPhone (Announced 2026-07-14)
A deep dive into PrismML's Bonsai 27B (July 14, 2026): post-hoc ternary (1.71 effective bits, 5.9GB, 94.6% retention) and 1-bit (1.125 bits, 3.9GB, 89.5%) builds of Qwen3.6-27B that run on an iPhone 17 Pro — with diagrams covering the quantization scheme, benchmarks, and what it means for on-device AI.
PrismMLBonsai 27B量子化