Ornith-1.5-35B-A3B for AI Agents: Setup and Performance
Ornith-1.5-35B-A3B: a 35B MoE with 3B active. Ollama run command, hardware by quant, OpenClaw setup, and benchmarks vs Qwen3.6 and Qwen3.5.
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Ornith-1.5-35B-A3B: a 35B MoE with 3B active. Ollama run command, hardware by quant, OpenClaw setup, and benchmarks vs Qwen3.6 and Qwen3.5.
LM Studio vs Ollama, October 2026: Ollama now runs MLX on Macs and both run headless. Where each wins on GPU Docker, concurrency, MCP and agent backends.
Building RAG from Scratch: No Frameworks Needed Understand Retrieval-Augmented Generation by building it yourself — pure Python, zero dependencies. Introduction LangChain, LlamaIndex, Haystack — great tools, but they hide how RAG actually works.
Build a loop where Rampart redacts personal details on your machine, Tabstack researches the redacted question, and your own model writes the reply. Four short Python files.
A Reddit user bought a nine-GPU Nvidia P106-100 mining rig with 54GB of VRAM for $35 and ran Qwen3.6-35B-A3B on it locally.
If you use a local model for classification, you know the wait: seconds per message, for questions it has answered hundreds of times. shad0w sits in front of any OpenAI-compatible server (Ollama works out of the box: llm="ollama/llama3.1" or `shad0w proxy --upstream http://localhost:11434/v1`),…
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass What if AI could help you spend less time looking at a screen and more time enjoying the world outside?
You face high cloud bills when you run powerful AI agents every day. Qwen3.5 gives you frontier-level multimodal reasoning locally. You combine it with OpenClaw for persistent agent workflows and Ollama for simple local serving.
GPT-6 Sol and Claude Sonnet 5 both cost $2/$10. Astra and Fable 5.1 both cost $10/$50. Where the bills still differ: caching, long context, budget tier.
The top launches, skills and plugins, multi agent moves, rising repos and arguments in coding agents on 12 Oct 2026, each with its source.
Concerns about privacy, reproducibility and cost are prompting scientists to use models on their computers rather than in the cloud.
M3 runs via Ollama Cloud or needs 75GB+ local. Qwen 3.7 has no open weights yet. Here's what actually works today for local agents.
Article URL: https://betterwispr.com/ Comments URL: https://news.ycombinator.com/item?id=50042333 Points: 6 # Comments: 1
Lumen's Black Lotus Labs says PoeLLM malware has hit more than 3,400 servers, most of them exposed AI tools like LiteLLM and Ollama.
According to LinkedIn job postings from Q4 2024, AI agent engineer roles increased 340% year-over-year, yet most require deploying on expensive cloud infrastructure.
San Francisco-based Deep Cogito used Runpod infrastructure to train Cogito v1, a high-performance open model family aiming at artificial.
AI Agents for Beginners, Part 1 The post Build Your First AI Agent with One Tool Call appeared first on Towards Data Science.
AWS’s new decision model comes with a familiar address. Released October 1, Strands Decider 2B is an open-weight model built The post AWS, Upstage and Ollama agree on a decision-model API. OpenAI hasn’t signed on. appeared first on The New Stack.
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