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Alternatives

Products that do what FindLLM does

Compare AI models, open source LLMs, and AI agents

  1. 1
    LLM Stats308

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  2. 2

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  3. 3

    Find your best LLM for a local inference

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    Vibe-check many open-source and proprietary LLMs at once

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  9. 9FT

    2024 · github.com

  10. 10

    Calculate and compare the cost of the latest LLM APIs

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  11. 11OS

    Hi everyone, we’re a small team, supported by Mozilla, who are working on re-imagining a UI for training, tuning and testing local LLMs. Everything is open source. If you’ve been training your own LLMs or have always wanted to, we’d love for you to play with the tool and give feedback on what the future development experience for LLM engineering could look like.

    2025 · github.com

  12. 12

    Track and improve your visibility on AI Search

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  13. 13

    The ultimate LLM comparison tool

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  14. 14IB

    Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…

    Oct 2025 · github.com

  15. 15FT

    Hey HN! When implementing an AI-powered feature for a project, we—and many people we've talked to—often reach a point where we have to choose an AI model but aren’t sure which one best fits our constraints or where to even start. Unfortunately, the advice to "just use chatgpt" is not always a good one. What if I want an open-source model? What languages does it support? What about context window size or the number of parameters? There are thousands of AI models already out there and many of them are perfect for certain problems. That’s why we’ve carved out this part of our product as a free…

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  16. 16DO
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  21. 21

    Reproducible benchmarks for evaluating AI models

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  22. 22

    See how the top LLMs talk about your brand

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  23. 23AG

    I’ve been building LLM tooling for a small VC fund and found myself explaining the same mental model over and over to non-technical people around me: how a stateless LLM becomes a chatbot, how tool use works, what an agent is mechanically, and why context windows shape all of it. I never found a guide that covered that full chain at the level I wanted, so I wrote one. It’s nine short chapters, each building on the last. Deliberately simplified: the goal is a useful mental model, not a textbook. Feedback, corrections, and contributions welcome: github.com/ymyke/aiaiai

    Apr 2026 · aiaiai.guide

  24. 24HT

    2023 · opensourceconnections.com

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