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Alternatives

Products that do what DBRX does

A new state-of-the-art open LLM

  1. 1
    AskCodi230

    Custom LLMs, without training. Use via openai compatible api

    Nov 2025

  2. 2

    Test-driven development for LLMs

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  3. 3

    AI prompt engineering business model guide

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  4. 4
    Dream 7B191

    Powerful Open Diffusion LLM, Beyond Autoregressive

    2025

  5. 5

    Open source data labelling platform for AI model tuning

    2023

  6. 6

    Find your best LLM for a local inference

    2023

  7. 7

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

    2024

  8. 8
    Taylor AI118

    Fine-tune open source LLMs in minutes

    2023

  9. 9

    New open-source LLM that rivals o3 in coding & reasoning

    2025

  10. 10

    The fast, easy and cheap OpenAI alternative

    2023

  11. 11
    Aqueduct107

    The easiest way to run open source LLMs

    2023

  12. 12
    Colossal135

    Effortlessly integrate tool-using agents with a single fetch

    2025

  13. 13

    LLM Provider arbitrage to get the best performance for the $

    2025

  14. 14

    Trace LLM requests + costs with OpenTelemetry monitoring

    Oct 2025

  15. 15

    Build local LLMs using top data science libraries

    2023

  16. 16

    API for LLM enabled knowledge ingestion and retrieval

    2024

  17. 17OS

    We’re building an open-source tool that makes it easy to expose secure, LLM-optimized APIs on top of your structured data—without manually designing endpoints or worrying about compliance. AI agents and LLM-powered applications need structured access to data, but traditional APIs and databases weren’t built with AI workloads in mind. Our tool automatically generates APIs that: - Filter out PII & sensitive data to comply with GDPR, CPRA, SOC 2, and other regulations. - Provide traceability & auditing, so AI apps aren’t black boxes, and security teams stay in control. - Optimize for AI…

    2025 · github.com

  18. 18

    One AI API for production - streaming, failover, logs

    Jan 2026

  19. 19

    Reproducible benchmarks for evaluating AI models

    12d ago · github.com

  20. 20NH

    Hey HN! When I started looking into LLMs and agents for software development and introducing them at work, I quickly realised that a person new to the topic faces a real barrage: - all the hype (AGI, engineers getting replaced by AI etc.) - conflicting opinions in virtually every discussion—for every person saying they’ve 10x-ed their productivity, there is a comment decrying LLMs as an utter failure - a lot of jargon (MoE, MCP, RAG, distillation, quantisation etc. etc.) - a profusion of models, IDEs/IDE extensions, CLI agents, other tools etc. Sorting through all of this can be quite…

    2025 · nohypeai.dev

  21. 21NL

    Built this because I was tired of every AI tool shipping my data to someone else server n0x runs the full stack LLM inference via WebGPU, autonomous ReAct agents, RAG over your own docs, sandboxed Python execution via Pyodide all inside a single browser tab. No account No keys No backend Models download once, cache in IndexedDB permanently. Biggest challenge was context window budgeting for the agent loop and making the WASM vector search non-blocking. Happy to talk architecture. GitHub: https://github.com/ixchio/n0x | Live demo: https://n0x-three.vercel.app

    Mar 2026 · n0xth.vercel.app

  22. 22OK

    We release an open source version of Andrej Karparthy's open knowledge base, and we scale it to support long PDFs with Pageindex. Any feedback is welcome to help us improve this project! Github repo: https://github.com/VectifyAI/OpenKB

    Apr 2026

  23. 23TM
  24. 24AG

    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

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