Y Combinator Open-Sources QM, Its Internal AI Agent Harness
Y Combinator released QM, an MIT-licensed tool it built to run AI agents across its own accounting, legal, and engineering teams, so any company can now self-host it.
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Every AI News story tagged with both Open-Source AI and AI Tools — the two topics side by side, updated as new articles publish.
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Y Combinator released QM, an MIT-licensed tool it built to run AI agents across its own accounting, legal, and engineering teams, so any company can now self-host it.
Read more →Poolside's new 118-billion-parameter Laguna S 2.1 matches or beats far larger rivals on agentic coding benchmarks and ships under an open license.
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Hugging Face is the open platform where most of the AI industry shares, hosts, and downloads models, datasets, and demo apps — often called the "GitHub of machine learning."
Read more →PrismML has released Bonsai 27B, a 27-billion-parameter open-weight model compressed to under 4GB, small enough to run natively on a phone while keeping most of its reasoning ability.
Read more →Mira Murati's startup released Inkling, a 975-billion-parameter open-weight model built for developers to fine-tune and adapt, rather than to top leaderboards.
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DeepSeek is the Chinese AI lab whose cheaply trained, open-weight models triggered Nvidia's biggest one-day stock drop and reshaped how the industry talks about AI costs.
Read more →Ollama, the open-source tool for running AI models locally, has raised $65 million in Series B funding, bringing total funding to $88 million as its developer base nears 9 million.
Read more →Meta now builds two separate AI model families: the open-weight Llama and the new proprietary Muse. Here's how they differ, and how to try either one.
Read more →GLM is the open-weight AI model family from Chinese lab Zhipu AI (Z.ai) — free to download and self-host, and competitive with top US models at a fraction of the API cost.
Read more →Mistral's new open-source model for Lean 4 fully saturates the miniF2F theorem benchmark, solves 87% of graduate-level math tests, and found five previously unknown bugs in production code — at roughly $4 per proof versus $300 for competing systems.
Read more →Chinese technology company Meituan has released LongCat-2.0, a 1.6-trillion-parameter coding model trained entirely on domestic Chinese chips, under the MIT License — the first frontier-class open-source model built without Western semiconductors.
Read more →Open-weight AI models release their trained parameters publicly so anyone can download, run, or fine-tune them — unlike closed models such as GPT-4 or Gemini, which are accessible only through paid APIs. Here is what that difference means in practice.
Read more →Qwen (Tongyi Qianwen) is Alibaba Cloud's family of open-weight AI models — covering language, code, vision, audio, and more — and the world's most-downloaded AI model series as of 2026.
Read more →Open-source AI models release their trained weights publicly, letting anyone run, study, or customize them without paying API fees. This guide explains what that means in practice and how to get started.
Read more →Liquid AI released LFM2.5-230M, a 230-million-parameter open-weight model that runs AI agent tasks at 213 tokens per second on a phone CPU and 42 tokens per second on a Raspberry Pi — without a cloud connection.
Read more →Chinese lab Zhipu AI has open-sourced GLM-5.2, a 753-billion-parameter model that outperforms GPT-5.5 on software engineering benchmarks while costing roughly one-sixth as much.
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