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Alternatives

Products that do what 0rka does

The full power of every model. Configured your way.

  1. 1SM

    We built a model router that plugs into coding agents (e.g. Claude Code, Codex, Cursor, etc.) and intelligently sends requests to the best model to serve them. Here's a quick demo of running it locally: https://www.youtube.com/watch?v=isKhAyivtfM. At Weave, we write most of our code with AI, and it's been getting more expensive. This came to a head when Opus 4.7 was released and, thanks to its tokenizer changes, our costs shot up. We knew we didn't need Opus for everything but we didn't want to lose out on the intelligence for the cases where you really need it. So we decided…

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  2. 2GA

    Hi, I’m Jakub, a solo founder based in Warsaw. I’ve been building GoModel since December with a couple of contributors. It's an open-source AI gateway that sits between your app and model providers like OpenAI, Anthropic or others. I built it for my startup to solve a few problems: - track AI usage and cost per client or team - switch models without changing app code - debug request flows more easily - reduce AI spendings with exact and semantic caching How is it different? - ~17MB docker image - LiteLLM's image is more than 44x bigger ("docker.litellm.ai/berriai/litellm:latest" ~…

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  3. 3

    One API for all AI models

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  4. 4

    Route every LLM call to the cheapest model that holds quality. Chatbots, RAG, agent loops, and finance. Cut spend 40 to 80 percent, measured on our own traffic, live in thirty seconds.

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  5. 5AL

    We built any-llm because we needed a lightweight router for LLM providers with minimal overhead. Switching between models is just a string change : update "openai/gpt-4" to "anthropic/claude-3" and you're done. It uses official provider SDKs when available, which helps since providers handle their own compatibility updates. No proxy or gateway service needed either, so getting started is pretty straightforward - just pip install and import. Currently supports 20+ providers including OpenAI, Anthropic, Google, Mistral, and AWS Bedrock. Would love to hear what you think!

    2025 · github.com

  6. 6

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  7. 7VA
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    OpenHunt154

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  10. 10
    RouKey98

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  11. 11

    All the AI models you need. One simple workspace.

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  12. 12KS

    Hi everyone, I run a generative AI infra company, unified API for 600+ models. Our team started deploying AI agents for our marketing and lead gen ops: content, engagement, analytics across multiple X accounts. OpenClaw worked fine for single agents. But at ~14 agents across 6 accounts, the problem shifted from "how do I build agents" to "how do I manage them." Deployment, monitoring, team isolation, figuring out which agent broke what at 3am. Classic orchestration problem. So I built klaw, modeled on Kubernetes: Clusters — isolated environments per org/project Namespaces — team-level…

    Feb 2026 · github.com

  13. 13
    Mycelis69

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  14. 14

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  15. 15OS

    Large Language Models (LLMs) are powerful, but they’re limited by fixed context windows and outdated knowledge. What if your AI could access live search, structured data extraction, OCR, and more—all through a standardized interface? We built the JigsawStack MCP Server, an open-source implementation of the Model Context Protocol (MCP) that lets any AI model call external tools effortlessly. Here’s what it unlocks: - Web Search & Scraping: Fetch live information and extract structured data from web pages. - OCR & Structured Data Extraction: Process images, receipts, invoices, and handwritten…

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  16. 16BL

    Hello everyone! I am Jan, CTO and one of the creators of Pathway, the real-time data processing framework. I’m excited to share Pathway’s ready-to-use AI Pipelines, configurable with just YAML! These frameworks offer out-of-the-box solutions for AI search, RAG, and more—optimized for real-time indexing and in-memory processing. What makes it simple? YAML templates! The pipeline templates are fully customizable using YAMLs to fit your needs, from changing the data sources to the choice of the LLM model, all without touching Pathway’s Python code. Thanks to the Pathway data processing engine,…

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  17. 17

    Fail-closed routing and safe execution for AI agents

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  18. 18
    Bloc3

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  19. 19

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    27d ago · leanroute.dev

  20. 204D

    this is an open-source project. the MVP to end all MVPs. made by me, a teenage developer angry at FAANG employees for creating a soulless, consumer-oriented world. The future is in creation, and the future is in teaching people to slam shit together with ChatGPT. Welcome to the start. :P

    2024 · 48hr.dev

  21. 21

    One API. Any Model. Anywhere.

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  22. 22S5
  23. 23CA

    TL;DR: we built a framework-agnostic agent runtime that uses gVisor for isolation and runs on k8s. It’s open-source under AGPLv3 Recently we’ve been working on a customer support “AI assistant” - essentially an interactive knowledge base/L1 support but with an option to touch resources that belong to a customer it’s talking to. We found existing tools to be lacking in these aspects: 1. Fully intercepted i/o. We wanted to trace out LLM calls as well as any other networking calls attempted by the harness so that guardrails and audit trails apply to all current and future systems…

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  24. 24IB

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