#GGUF vision model
52 related articles
·2 min
Unsloth v0.1.461-beta: Fix for Local GGUF Vision Model Loading
Unsloth v0.1.461-beta fixes local GGUF vision model loading on llama-server in Studio, adds variant directory companion file lookup for stable multimodal deployment.
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·2 min
Deploying an iMessage AI Assistant on Raspberry Pi: Building a Home-Resident Smart Agent
iMessage Hermes is an open-source project deploying AI agents on Raspberry Pi, enabling iMessage and SMS interaction via real phone numbers. A deep dive into its architecture and potential.
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·4 min
Project Rai-chan Technical Breakdown: A Complete Guide to Building a Fully Local AI Companion
Deep dive into Project Rai-chan's tech stack: Ollama+Gemma local LLM, Unity rendering, VOICEVOX speech synthesis, and more — exploring the technical path for local AI companions.
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·3 min
Kimi K3 vs Claude Real-World Test: Near-Equal Performance at 1/8 the Price
Real-world comparison of Kimi K3 vs Claude flagship across e-commerce pages, 3D fighting games, and flight simulators. Kimi K3 delivers 90% output quality at 1/8 the price with faster speeds and local deployment support.
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·3 min
Ollama's Extra Charges for Kimi 3 Spark Community Controversy: Should Open-Source Models Be Free to Use?
Ollama lists Kimi 3 with extra pay-per-use fees, breaking subscription expectations and sparking debate over open-weight models and AI service pricing tiers.
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·3 min
DeepSeek-OCR Deployment & Fine-Tuning in Practice: From vLLM Inference to Unsloth Fine-Tuning
Complete guide to DeepSeek-OCR from vLLM inference deployment and Unsloth model loading to fine-tuning, covering cloud server setup, GPU selection, and code examples — all on a single 4090 GPU.
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·3 min
Build RAG and AI Agent Projects at Zero Cost: A Practical Guide to Open-Source Tools
Build high-quality AI projects on a budget. Learn how to use Ollama, Groq, Chroma, and other free open-source tools to build RAG systems and multi-Agent workflows from scratch.
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·3 min
Build RAG and AI Agent Projects at Zero Cost: A Practical Guide to Open-Source Tools
Build high-quality AI projects on a budget. Learn how to use Ollama, Groq, Chroma, and other free open-source tools to build RAG systems and multi-Agent workflows from scratch.
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·7 min
DIY Companion Robot: Building Your AI Desktop Buddy with Jetson Orin
A maker builds a DIY companion robot with NVIDIA Jetson Orin and 4S LiPo battery. Explore the full development journey from first power-up to AI interaction, including edge computing, power design, and companion robot trends.
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·5 min
China Weighs Restricting Top AI Model Exports as DeepSeek Develops Its Own Inference Chip
China's Commerce Ministry weighs restricting overseas access to top open-weight AI models from Alibaba, ByteDance, and DeepSeek, while DeepSeek develops its own inference chip amid a US-China AI export standoff.
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·5 min
China Weighs Restricting Top AI Model Exports, While DeepSeek Quietly Builds Its Own Inference Chip
China's Ministry of Commerce is weighing restrictions on overseas access to top open-weight AI models from Alibaba, ByteDance, and DeepSeek. Meanwhile, DeepSeek is quietly building its own inference chip and raising ~$7B in first external funding.
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·3 min
27B Parameter LLM on an iPhone? A Deep Dive into On-Device Full-Parameter AI
Startup Prismo claims to compress a 27B-parameter model to 4GB for full local inference on iPhone 17 Pro. We break down the compression tech, compare it to Apple's MoE approach, and assess real-world limits.
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·3 min
Ornith 9B/35B Hands-On: A New Local Deployment Option for Code Agents
Ornith 1.0 by Deep Reinforce reinforces Qwen 3.5 for code agents. We test Ornith 9B & 35B MoE on Chinese writing, logic, and invoice OCR, with full llama.cpp deployment guide.
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·3 min
Claude Opus 5 Launch Imminent, Alibaba Qwen Officially Integrated into Apple Intelligence
Claude Opus 5 launches next week; Alibaba Qwen integrates into Apple Intelligence for Chinese users; 27B on-device model compressed to 3.8GB; open-source models narrow gap to closed-source by 3.3%.
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·3 min
Running a 27B Model on iPhone: How 1-bit Quantization Achieves Extreme Compression
PrismML's Bonsai compresses a 27B model from 54GB to 3.9GB, running at ~11 tokens/sec on iPhone. A deep dive into QAT, knowledge distillation, and speculative decoding.
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·2 min
Abliteration Explained: Building a Custom Uncensored Text Encoder for Krea 2
How a developer ran 4,000 multi-seed abliteration trials to build a 100% HarmBench-compliant uncensored text encoder for Krea 2's Qwen3-VL-4B, with five quantization formats and ComfyUI deployment guide.
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·2 min
GLM Open-Source Model: Can a Million-Token Context Window Challenge Claude Code?
GLM open-source LLM claims 1M-token context, local deployment, and coding ability rivaling Claude Code. We break down the three key selling points and evaluate the hype vs. reality.
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The Guardian Angels Framework: How LLM…
·3 min
The Guardian Angels Framework: How LLM Personalization Can Achieve Both Efficiency and Data Security
The Guardian Angels framework shows how LLM personalization can achieve both productivity and data security through local deployment, differential privacy, and tiered permissions.
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Java Local LLM Inference: Low-Latency …
·2 min
Java Local LLM Inference: Low-Latency LLM Deployment with Panama FFM
Learn how Java and OpenJDK Panama FFM API enable local LLM inference. Explore the technical foundations, JVM ecosystem benefits, and low-latency AI deployment in enterprise Java systems.
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Inkling Open-Weights Model: A New Expl…
·2 min
Inkling Open-Weights Model: A New Exploration in the Open-Source AI Ecosystem
Inkling open-weights model released. Explore the key difference between open-weights and fully open-source AI, Inkling's positioning, and how to choose the right open-source LLM for production.
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