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Alternatives

Products that do what Rayline routes Claude Code subagents to on-device and cheaper models does

Hi HN, I’m one of the builders of Rayline. Rayline is a Claude Code compatible LLM gateway. It intercepts and overrides claude code’s internal routing and lets you route subagent calls to different models instead. For example, you can run the main agent on Opus, some subagents on cloud-hosted open models, and other subagents on-device. We’ve seen others implement routing for claude code as tools the agent can invoke. In our experience, that doesn’t work well because it requires the main agent to use tokens to think about + call the tools, and LLMs are generally a very inefficient way to make…

  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…

    Jun 2026 · github.com

  2. 2FO
  3. 3

    Our most intelligent model to date

    2025 · anthropic.com

  4. 4ST

    I've been working on CloudRouter, a skill + CLI that gives coding agents like Claude Code and Codex the ability to start cloud VMs and GPUs. When an agent writes code, it usually needs to start a dev server, run tests, open a browser to verify its work. Today that all happens on your local machine. This works fine for a single task, but the agent is sharing your computer: your ports, RAM, screen. If you run multiple agents in parallel, it gets a bit chaotic. Docker helps with isolation, but it still uses your machine's resources, and doesn't give the agent a browser, a desktop, or a GPU to…

    Feb 2026 · cloudrouter.dev

  5. 5

    Open-source unified interface for agent harnesses

    21d ago · harnessrouter.ai

  6. 6AL

    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

  7. 7
    Agihalo68

    LLM Router for A.I Agent & Saas with x402

    Jan 2026

  8. 8

    Trajectory-aware LLM routing that cuts agent cost

    10d ago · iq-routing.com

  9. 9
    Replicas239

    Run Claude Code and Codex in the cloud

    Jun 2026 · replicas.dev

  10. 10CC

    Hello everyone. Claudraband wraps a Claude Code TUI in a controlled terminal to enable extended workflows. It uses tmux for visible controlled sessions or xterm.js for headless sessions (a little slower), but everything is mediated by an actual Claude Code TUI. One example of a workflow I use now is having my current Claude Code interrogate older sessions for certain decisions it made: https://github.com/halfwhey/claudraband?tab=readme-ov-file#s... This project provides: - Resumable non-interactive workflows. Essentially `claude -p` with session support: `cband continue…

    Apr 2026 · github.com

  11. 11
    KarmaBox318

    Run your own Claude Code in your pocket.

    Apr 2026

  12. 12

    Make Claude Code faster and cheaper without losing context

    Mar 2026

  13. 13
    agmsg245

    Stop copy-pasting between your AI coding agents

    Jun 2026 · github.com

  14. 14

    Connect Claude Code to your internal systems w/o credentials

    Mar 2026

  15. 152C

    Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…

    Feb 2026 · github.com

  16. 16

    Tokens are money. Save both.

    16d ago · router.com

  17. 17RT

    This project (Agents Observe) started as an exploration into building automation harnesses around claude code. I needed a way to see exactly what teams of agents were doing in realtime and to filter and search their output. A few interesting learnings from building and using this: - Claude code hooks are blocking - performance degrades rapidly if you have a lot of plugins that use hooks - Hooks provide a lot more useful info than OTEL data - Claude's jsonl files provide the full picture - Lifecycle management of MCP processes started by plugins is a bit kludgy at best The biggest takeaway is…

    Apr 2026 · github.com

  18. 18AR

    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

  19. 19

    Optimize Performance, Cost, Speed & Carbon for each prompt

    Nov 2025

  20. 20FC

    Just to clarify the background a bit. This project wasn’t planned as a big standalone release at first. On January 16, Ollama added support for an Anthropic-compatible API, and I was curious how far this could be pushed in practice. I decided to try plugging local Ollama models directly into a Claude Code-style workflow and see if it would actually work end to end. Here is the release note from Ollama that made this possible: https://ollama.com/blog/claude Technically, what I do is pretty straightforward: - Detect which local models are available in Ollama. - When…

    Jan 2026 · github.com

  21. 21

    Dev tool that worries about your LLM API failures.

    Aug 2026 · llmrouter.dpdns.org

  22. 22

    Hey HN! We are building HarnessRouter, a canonical API for running Codex, Claude Code, Hermes, and other managed agent harnesses as your product backend. Before building HarnessRouter, I used to build our own agent harness for our products. I tried LangGraph, agent SDKs from different vendors, pydantic, LLM tool use / function call, and so on. It's a very heavy lifting engineering effort, and I am disappointed about the agent deliveries compared to what Codex, CC can deliver. That changed my mindset. The frontier labs and famous open source communities are already putting so much…

    20d ago · github.com

  23. 23SP

    Hey HN, My cofounder and I have gotten tired of CC ignoring our markdown files so we spent 4 days and built a plugin that automatically steers CC based on our previous sessions. The problem is usually post plan-mode. What we've tried: Heavily use plan mode (works great) CLAUDE.md, AGENTS.md, MEMORY.md Local context folder (upkeep is a pain) Cursor rules (for Cursor) claude-mem (OSS) -> does session continuity, not steering We use fusion search to find your CC steering corrections. - user prompt embeddings + bm25 - correction embeddings + bm25 - time decay - target query embeddings -…

    Mar 2026 · gopeek.ai

  24. 24RA

    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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