Build Your Own Local AI Coding Agent with Gemma 4 and OpenCode

Using Gemma 4, Ollama, OpenAI Agents SDK, and Tavily MCP to build a lightweight research agent The post From Local LLM to Tool-Using Agent appeared first on Towards Data Science.

DeepReinforce released Ornith-1.0, an open-source coding model family built on Gemma 4 and Qwen 3.5. Instead of a fixed harness, the model learns its own scaffold during reinforcement learning. The 397B flagship reports 82.4 on SWE-Bench Verified, with all weights under the MIT license. The post DeepReinforce Releases Ornith-1.0: An Open-Source Coding Model Family That Learns Its Own RL Scaffolds appeared first on MarkTechPost.

This week, New York City is hosting AWS Summit, bringing together builders, customers, and AWS teams for a full day of announcements, demos, and technical sessions at the Javits Center. I wrote blog posts for some of the Summit launches, so I am excited to see them go live this week. I just won’t be […]

This article builds a full local agentic programming stack using Ollama, Gemma 4, and Claude Code.

Compare Gemma 4 edge formats: BF16, Q4_0 QAT, and mobile QAT, on published memory numbers and design tradeoffs. The post Google DeepMind Releases Gemma 4 QAT Checkpoints: Q4_0 and a New Mobile Format Cut On-Device Memory appeared first on MarkTechPost.

Gemma 4 12B uses a new encoding scheme and token prediction to punch above its weight.

In this article, we will go deep under the hood of Ollama's configuration engine, exploring how to fine-tune local language model parameters.

In this tutorial, we will give Gemma 4 two new tools and watch the model decide, on its own, when to look around and when to compute.