Topic
Ollama
8 episodes
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I built Andrej Karpathy's "LLM Council" on my own hardware, and now no single model gets the last word
Jessica and Cathy dig into a local rebuild of Karpathy's LLM Council and land on the real claim: the win is not voting, it's structured synthesis across models with different failure modes. They like the practical adaptation to Ollama on a single twelve-gigabyte GPU, but push on where the article overreaches and where the product value is actually real.
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You don't need an expensive GPU to run a local LLM that actually works
Cody and Justy examine the claim that you don't need an expensive GPU to run capable local LLMs. Cody opens skeptical about quantization trade-offs and real-world inference speed; Justy pushes back with the actual user story—cost-conscious builders and privacy-first home automation. They dig into what 'works' really means, explore the CPU-only vs. GPU trade-off, and land on a nuanced take: smaller quantized models on mid-range hardware are genuinely usable now, but marketing around this can oversell the experience. Build Next includes testing Ollama on a specific budget GPU and benchmarking a 7B quantized model on a CPU-only rig.
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How to Implement Tool Calling with Gemma 4 and Python MachineLearningMastery
Episode 287 of Exploring Next dives into the world of tool calling with Gemma 4 and Python, exploring how to build a local, privacy-first tool-calling agent.
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Running local models on Macs gets faster with Ollama's MLX support
Ollama just added MLX support for Apple Silicon Macs, promising significantly faster local LLM performance through better unified memory usage. We break down what this actually means, why it matters as local models gain momentum, and the technical architecture that makes it work.
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openclaw with ollama (Zero cost AI Assistant)
Izzo and Boone explore OpenClaw, an open-source AI assistant framework that runs entirely locally with Ollama. They dig into how it creates zero-cost AI workflows, the agent architecture with workspace management and subagent spawning, and why running your own AI stack locally matters for both privacy and cost control.
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LangGraph Explained from Scratch | Aman Kharwal
This episode dives into LangGraph, a new library that transforms how we build intelligent agents using Large Language Models. We'll explore its unique graph-based approach, practical applications, and why this matters for developers and users alike.
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Qwen3 VL · Ollama Blog
Qwen3-VL October 14, 2025 Qwen3-VL , the most powerful vision language model in the Qwen series is now available on Ollama’s cloud. The models will be made available locally soon.
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I switched from LM Studio/Ollama to llama.cpp, and I absolutely love it
I switched from LM Studio/Ollama to llama.cpp, and I absolutely love it Credit: By Dhruv Bhutani Published Nov 2, 2025 Dhruv Bhutani has been writing about consumer technology since 2008, offering deep insights into the personal technology landscape through features and opinion pieces. He writes for XDA-Developers, where he focuses on topics like productivity, networking, self-hosting, and more.