Alternatives
Products that do what Lambda-G Optimiser does
Route optimizer within 0.13% of LKH-3. One API call
- 1P3
2019 · github.com
- 2RO
2014 · routific.com
- 3SM
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
- 4IW
Hi HN! During the last few years, I worked on a few applications built with Go, running on AWS Lambda. As I got to know the platform better, I started to find Go & Lambda to be a really productive combination. The applications were fast, and they ended up being much cheaper to run than what my team & I had built before. It’s probably not the best platform for _every_ application, but I was surprised at how much of our workload worked well on it. As we brought new engineers on to our team and helped them get up to speed with the stack, I found that we were covering a lot of the same topics…
2021
- 5
Hi HN, we built world-model-optimizer, an open source tool to continually improve a specialized model for an agent. It does this by simulating production tool responses through text world modeling (similar to QwenAgentWorld, summary here https://x.com/silennai/status/2073887455884058814). We can then use this to train a router for frontier, OS, and local models (use defaults or pick which ones to optimize against). wmo ingests agent traces, builds the simulation, embeds the traces, runs different models you choose against the simulation scenarios, and then uses a KNN…
Jul 2026 · github.com
- 6SL
2017 · github.com
- 7PI
OP here. Most Deep Learning approaches for TSP rely on pre-training with large-scale datasets. I wanted to see if a solver could learn "on the fly" for a specific instance without any priors from other problems. I built a solver using PPO that learns from scratch per instance. It achieved a 1.66% gap on TSPLIB d1291 in about 5.6 hours on a single A100. The Core Idea: My hypothesis was that while optimal solutions are mostly composed of 'minimum edges' (nearest neighbors), the actual difficulty comes from a small number of 'exception edges' outside of that local scope. Instead of…
Dec 2025
- 8TC
Hey HN, I’m sharing ts-chan, an NPM package providing Go-like concurrency primitives, including channels and select statements, for TypeScript and JavaScript, supporting Node.js, Deno, Bun, and browsers. This is something I've built to make implementing Go-style "control loops" feasible in JavaScript, but there are many possible applications. Highlights: - Features a FIFO processing Chan class and versatile Select class for concurrency control. - Supports buffered channel and channel close semantics very close to Go's. - TypeScript-first implementation. - Defines a simple "channel protocol"…
2023 · github.com
- 9LA
2022 · woodrush.github.io
- 10AF
I built an unofficial CLI and MCP server for Lambda cloud GPU instances. The main idea: your AI agents can now spin up and manage Lambda GPUs for you. The MCP server exposes tools to find, launch, and terminate instances. Add it to Claude Code, Cursor, or any agent with one command and you can say things like "launch an H100, ssh in, and run big_job.py" Other features: - Notifications via Slack, Discord, or Telegram when instances are SSH-ready - 1Password support for API keys - Also includes a standalone CLI with the same functionality Written in Rust. MIT licensed. Note: This is an…
Jan 2026 · github.com
- 11AL
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
- 12LA
2017 · lambdacult.com
- 13
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IQ Routing▲100Route 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.
11d ago · iq-routing.com
- 16RF
Hi HN! I built Routing24 to make route optimization easier and accessible for small businesses and solo drivers. With Google Maps, you can plan routes between a few locations for free, but it doesn’t support efficient multi-stop planning, handling multiple vehicles, or adding specific business rules like delivery time windows. Many tools offer route optimization for around $30 per vehicle per month, but Routing24 provides it completely free. Optimization happens fully on the client-side, using your device’s resources instead of cloud servers. The interface is simple for now: you can…
2024 · routing24.com
- 17OA
2021 · optimule.com
- 18GV
2018 · github.com
- 19OA
https://github.com/gugarosa/opytimizer Did you ever reach a bottleneck in your computational experiments? Are you tired of selecting suitable parameters for a chosen technique? If yes, Opytimizer is the real deal! This package provides an easy-to-go implementation of meta-heuristic optimizations. From agents to search space, from internal functions to external communication, we will foster all research related to optimizing stuff. Use Opytimizer if you need a library or wish to: - Create your optimization algorithm; - Design or use pre-loaded optimization tasks; -…
2021
- 20LLambdaway▲29
I am working on this project, http://epsilonwiki.free.fr/lambdaway/, and would be happy to get your opinion back. Thanks a lot. Alain Marty
2016
- 21LA
We have released a high-performance CMS (2-10ms in our tests) CMS, that needs to be set-up by a programmer. Enjoy! EDIT: Since links in a text post do not become clickable, I've moved them to the comments.
2015
- 22AT
I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com
- 23AT
Dec 2025 · graphhopper.com
- 24AL
2017 · github.com
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