ModelPointer
Open-source AI Gateway for enterprise LLM infrastructure
What it does
Unlike traditional API gateways or simple LLM proxies, ModelPointer is an enterprise AI Gateway built in Rust for high performance. It is designed natively for LLM traffic with model-aware routing, API key management, RPM/TPM rate limiting, and observability. Hybrid-cloud ready, it can automatically burst traffic from self-hosted models to cloud providers when local capacity is exhausted.
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We built open OpenRouter that turns usage into a better model10d ago · github.com · ▲220Hi HN, we built an open source model gateway. It's a single place to manage our own self hosted, frontier, and open source models in one place. It’s is rust native, built for concurrency, and implements all the config quirks across models and providers (streaming formats, tool calls, model parameters, rate limits, and different error behavior). The gateway adds under 1 ms for BYOK requests and under 2 ms when Experiential supplies the provider key. It has every major inference provider, and 1000+ models refreshed daily via a codex agent that opens a PR. Compared to other similar projects…
- GAGoModel – an open-source AI gateway in GoApr 2026 · github.com · ▲217
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" ~…
- ARArch-Router – 1.5B model for LLM routing by preferences, not benchmarks2025 · ▲66
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…
- ALA lightweight AI gateway to 100+ models, in TS2024 · github.com · ▲37
We are Rohit & Ayush, we created Portkey this year March to help tackle some challenges we had seen while building apps based on GPT3, 3.5, 4, and the DevOps principles we brought to the scene to help tackle them. We believe, a solid, performant, and reliable gateway lays the foundation to help build the next level of LLM apps. It decreases excessive reliance on any one company and takes the focus back to building instead of spending time fixing the nitty gritties of different providers and making them work together. Features: Blazing fast (9.9x faster) with a tiny footprint (~45kb…
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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