A lightweight AI gateway to 100+ models, in TS
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…
A lightweight AI gateway to 100+ models, in TS launched on January 8, 2024 with 37 votes, #896 of 4,437 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 2 years on.
In plain words
Portkey is a lightweight TypeScript gateway that connects applications to over 100 AI models from multiple providers. It offers fast performance with a small footprint and includes load balancing, automatic failover, and retry logic to keep AI applications running reliably. Designed for developers building production AI apps, it reduces vendor lock-in and simplifies managing different AI providers and models in a single application.
written from the facts on this page · September 2026
From the sources
A blazing fast AI Gateway with integrated guardrails. Route to 1,600+ LLMs, 50+ AI Guardrails with 1 fast & friendly API. - Portkey-AI/gateway
In the maker’s words, at launch
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…
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An open-source AI Gateway with integrated guardrails2024 · github.com · ▲21Hi HN, I've been developing Portkey Gateway, an open-source AI gateway that's now processing billions of tokens daily across 200+ LLMs. Today, we're launching a significant update: integrated Guardrails at the gateway level. Key technical features: 1. Guardrails as middleware: We've implemented a hooks architecture that allows guardrails to act as middleware in the request/response flow. This enables real-time LLM output evaluation and transformation. 2. Flexible orchestration: The gateway can now route requests based on guardrail verdicts. This allows for complex logic like fallbacks…
LLM Gateway2025 · llmgateway.io · ▲296I built an OpenAI-compatible LLM gateway that routes requests to OpenAI, Anthropic, Ollama, vLLM, llama-server, SGLang... anything that speaks /v1/chat/completions. Single Go binary, one YAML config file, no infrastructure. It does the things you'd expect from this kind of gateway... semantic routing via a three-layer cascade (keyword heuristics, embedding similarity, LLM classifier) that picks the best model when clients omit the model field, weighted round-robin load balancing across local inference servers with health checks and failover. The part I think is most…
TrueFoundry AI GatewayDec 2025 · truefoundry.com · ▲315Many teams connecting LLMs to external tools eventually encounter the same architectural issue: as more tools and agents are added, the integration pattern becomes an N×M mesh of direct connections. Each agent implements its own auth, retries, rate limiting, and logging; each tool needs credentials distributed to multiple places and observability becomes fragmented. We built LLM gateway with this goal to provide a single place to manage authentication, authorization, routing, and observability for MCP servers, with a path toward a more general agent-gateway architecture in the future. The…

GoModel – an open-source AI gateway in GoApr 2026 · github.com · ▲217Hi, 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" ~…
We built open OpenRouter that turns usage into a better modelAug 2026 · github.com · ▲222Hi 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…
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