PrismML Bonsai — Does a 1.15GB 8B Model Actually Make Sense?
PrismML Bonsai, built by a Caltech-founded team, is a 1-bit LLM that represents weights using only {-1, +1}. An 8B model fits in 1.15GB and reportedly runs 8x faster than full precision.
Tags
local-llm
11 posts
I Ran Gemma 4 Locally — 8B Models Can Do Function Calling
I installed Google's Gemma 4 (Apache 2.0) via Ollama and tested Korean language, structured output, and function calling firsthand. Can a 9.6GB local model actually become a building block for agent pipelines?
GGML/llama.cpp Joins Hugging Face
The ggml.ai team joins Hugging Face to secure the long-term sustainability of llama.cpp. We analyze the structural changes and technical implications for the local AI inference ecosystem.
IQ*_K/IQ*_KS Quantization Merged into llama.cpp
IQ-series quantization methods developed in ik_llama.cpp are being merged into llama.cpp mainline. Learn about IQ2_K through IQ4_KS precision improvements and local LLM inference optimization.
Qwen3 Coder Next llama.cpp Graph Optimization
ggerganov restructures the llama.cpp compute graph to achieve up to 38% inference speedup for the Qwen3 Coder Next 80B model. Detailed benchmark analysis and technical breakdown.
DDR5 RDIMM vs RTX 3090 — The Cost-per-GB Tipping Point for Local LLMs
DDR5 RDIMM pricing has dropped below RTX 3090 VRAM per GB, marking a turning point in local LLM hardware decisions. We analyze CPU vs GPU inference cost structures.
Devstral Small 2 24B & Qwen3 Coder 30B
Mistral Devstral Small 2 24B and Qwen3 Coder 30B arrive simultaneously. A comparative analysis of small coding models that run on Raspberry Pi and the future of local AI coding.
Kitten TTS V0.8: Sub-25MB SOTA Speech for Edge Devices
A deep dive into Kitten TTS V0.8 — a 14M parameter, sub-25MB text-to-speech model matching cloud TTS quality. Analysis of edge deployment potential and the local voice AI trend.
Heretic 1.2: 70% VRAM Reduction via Quantization and MPOA Explained
Heretic 1.2 is here with 4-bit quantization cutting VRAM usage by up to 70% and MPOA delivering higher-quality abliteration. A deep dive into the latest cost-saving techniques for local LLM operations.
How to Run Qwen3-Coder-Next 80B on 8GB VRAM
Analyzing quantization and lazy loading techniques to run an 80B parameter coding AI model on consumer 8GB VRAM GPUs. Exploring the practicality and limitations of local LLM coding.
NVIDIA DGX Spark CUDA Compatibility Issues
NVIDIA DGX Spark sm121 CUDA failures analyzed — Triton breakage, FP4/FP6 missing, handheld chip allegations, and a buyer checklist for AI workstation shoppers.