Alternatives
Products that do what OpenPaths does
Open-source AI router with sub-ms GPU routing to 432+ models
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2015 · mapzen.com
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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…
Jun 2026 · github.com
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General Compute▲315AI models that run on an inference cloud optimized for speed
May 2026 · generalcompute.com
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Try it out! https://glhf.chat/ Hey HN! We’ve been working for the past few months on a website to let you easily run (almost) any open-source LLM on autoscaling GPU clusters. It’s free for now while we figure out how to price it, but we expect to be cheaper than most GPU offerings since we can run the models multi-tenant. Unlike Together AI, Fireworks, etc, we’ll run any model that the open-source vLLM project supports: we don’t have a hardcoded list. If you want a specific model or finetune, you don’t have to ask us for it: you can just paste the Hugging Face link in and…
2024 · glhf.chat
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Open source AI gateway turning traffic into a better model
3d ago · experientiallabs.ai
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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
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Turning Idle GPUs Into Enterprise AI Velocity
Feb 2026 · usechamber.io
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2025 · compare-openrouter-models.pages.dev
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Steiner is a series of reasoning models trained on synthetic data using reinforcement learning. These models can explore multiple reasoning paths in an autoregressive manner during inference and autonomously verify or backtrack when necessary, enabling a linear traversal of the implicit search tree. Blog: https://medium.com/@peakji/a-small-step-towards-reproducing-... Hugging Face: https://huggingface.co/collections/peakji/steiner-preview-67...
2024 · medium.com
- 19RA
I've been begrudgingly working on autorouters for 2 years, looking for new techniques or modern methods that might allow AI to create circuit boards. One of the biggest problems in my view for training an AI to do autorouting is the traditional grid-based representation of autorouting problems which challenges spatial understanding. But we know that vision models are very good at classifying, so I wondered if we could train a model to output a path as a classification. But then how do you represent the path? This lead me down the track of trying to build an autorouter that represented paths…
Feb 2026 · pattern-pathfinder.vercel.app
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Hi HN — we're the team behind Arch (https://github.com/katanemo/archgw), an open-source proxy for LLMs written in Rust. Today we're releasing Arch-Router (https://huggingface.co/katanemo/Arch-Router-1.5B), a 1.5B router model for preference-based routing, now integrated into the proxy. As teams integrate multiple LLMs - each with different strengths, styles, or cost/latency profiles — routing the right prompt to the right model becomes a critical part of the application design. But it's still an open problem. Most routing systems fall into two…
2025
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2025 · llmgateway.io
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This project began when I decided it would be easier to write an autorouter than route a 8000+ net backplane by hand. This is a KiCad plugin with a few different algorithms, the coolest of which is a 'Manhattan routing grid' autorouter that routes along orthogonal traces. The basic idea was to steal an algorithm from FPGA routing and apply it to PCBs. I'm using CuPy for speeding up the routing; CPU-bound is at least 10x slower than the GPU version. This is in a very pre-alpha state, but it does _technically_ work. It's not great by any measure but then again it is an autorouter. I have a…
Oct 2025 · github.com
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Our company Vertex.AI has been working on this for a while but this is the first public release. We're starting with using PlaidML to bring OpenCL support to Keras and more frameworks, platforms, etc are coming. Yes, this means you can use use your AMD GPU for deep learning dev. Sorry, no Mac or Windows support yet although the brave can try building from source (it should work). http://vertex.ai/blog/announcing-plaidml https://github.com/plaidml/plaidml
2017
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