Alternatives
Products that do what Incredible Small 1.0 by Incredible does
Agentic AI Models that can take 1000+ actions at once
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Related: https://simonwillison.net/2026/Jan/27/one-human-one-agent-on...
Jan 2026 · emsh.cat
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Powers faster, efficient reasoning for long-running agents
Jun 2026 · developer.nvidia.com
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2023 · tinyllms.vercel.app
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Hey HN, Anders and Tom here. We had a post about our AI test automation framework 2 months ago that got a decent amount of traction (https://news.ycombinator.com/item?id=43796003). We got some great feedback from the community, with the most positive response being about our vision-first approach used in our browser agent. However, many wanted to use the underlying agent outside the testing domain. So today, we're releasing our fully featured AI browser automation framework. You can use it to automate tasks on the web, integrate between apps without APIs, extract data, test…
2025 · github.com
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Hey HN, Anders and Tom here - we’ve been building an end-to-end testing framework powered by visual LLM agents to replace traditional web testing. We know there's a lot of noise about different browser agents. If you've tried any of them, you know they're slow, expensive, and inconsistent. That's why we built an agent specifically for running test cases and optimized it just for that: - Pure vision instead of error prone "set-of-marks" system (the colorful boxes you see in browser-use for example) - Use tiny VLM (Moondream) instead of OpenAI/Anthropic computer use for dramatically…
2025 · github.com
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Hello! We just released freeact (https://github.com/gradion-ai/freeact), a lightweight agent library that empowers language models to act as autonomous agents through executable code actions. By enabling agents to express their actions directly in code rather than through constrained formats like JSON, freeact provides a flexible and powerful approach to solving complex, open-ended problems that require dynamic solution paths. * Supports dynamic installation and utilization of Python packages at runtime * Agents learn from feedback and store successful code actions as…
2025 · github.com
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