
Decisor
Smart LLM routing to cut AI costs by up to 90%
Decisor launched on January 26, 2026 with 5 votes, #3,400 of 14,584 launches that month and more than 75% of that year's launches. The site was not reachable when checked in September 2026.
What it does
Decisor is a smart LLM router that automatically routes each request to the most cost-efficient model without sacrificing quality. Save up to 90% on LLM inference by using the right model for the right task — no manual tuning required.
Does a similar job
all alternatives →
FastRouter.ai22d ago · fastrouter.ai · ▲364Route requests to the right LLM for cost, latency & quality
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…
Smart model routing directly in Claude, Codex and CursorJun 2026 · github.com · ▲216We 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…
Any-LLM – Lightweight router to access any LLM Provider2025 · github.com · ▲125We 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!


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