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Levi

run AlphaEvolve on your Claude Code/Codex for dirt cheap

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Hi HN,Wanted to share something I'm excited about.I’ve been fascinated by AlphaEvolve and its results for more than a year now, but using open source frameworks seems overwhelming because of the high costs. I can’t really afford hundreds of Claude Opus calls every time I want to run it. I want to be able to try it out many times and all sorts of unique domains. What if it was possible for AlphaEvolve to be much more affordable while getting a better performance? .Over the last six months or so, I’ve been working on LEVI, an open source AlphaEvolve-like system that can outperform existing open source frameworks at a fraction of the cost (upto 35x cheaper!). It can also run on Claude Code or Codex, making it even more accessible (I've mostly been using it with a QWEN-30B). LEVI comes in two flavors where I felt it’ll make the most difference: Code Optimization, and Prompt Optimization (sorry math, you got a less direct path; workable through the code route).The core thesis behind LEVI is that with the right search architecture, smaller models can substitute for or outperform larger ones. This means it’s much more economical to rely on smaller models for most of the work. That’s the entire takeaway. Making this work in practice is a different problem, but if you forget everything else from this post this is the only message I think I’m really trying to convey here.LEVI does it in three ways: 1) Invest in solution diversity from the start and ensure its maintained. We don’t want to converge to the same solution, especially with smaller models in the mix, and rely on large models to pull us out of the basin. 2) Use smarter routing across larger and smaller models (i.e. most mutations don’t require a Claude Opus X) 3) For prompt optimization not every rollout is as important. Build a proxy subset to approximate.I’ve tried LEVI on systems problems (like MoE scheduling or database transaction scheduling) and found that LEVI outperforms existing frameworks on almost every problem I threw at it while consistently using a smaller budget (unto 7x cheaper). For prompt optimization, across problems like IFBench and HotSpotQA, LEVI reaches a similar or better score as GEPA while using less than half the rollouts!Happy to answer any questions or take any suggestions! If there are unexpected or niche domains where this can be applied, I would love to hear.Technical Blog: https://ttanv.github.io/levi/ GitHub: https://github.com/ttanv/levi

HN · launched Jun 8, 2026 · 5 upvotes (top 87%) · 0 views

Niche: llm optimization tools · 127 launches, 9 in the last 7 days ▲ +50% · Explore this niche →

Category and tags

  • Horizontal
  • Dev tools
  • Developer
  • AI-native
  • Commercial product

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Could you build this?

Partial The UI and LLM orchestrator script can be vibe-coded, but implementing the search algorithms and evolutionary prompt/code refinement logic from AlphaEvolve requires understanding complex search architectures.

What it would actually take: The system combines code generation loops with genetic algorithms and tree search (such as Monte Carlo Tree Search or evolutionary Pareto optimization) over code diffs, integrated via the Anthropic Claude API. The difficult part is building an effective evaluation sandbox, mutation operators, and cost-effective search pruning heuristics to run evolutionary searches on smaller model budgets.

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Competitors

Other products that read as similar to this one : 354 launches clear the similarity bar, closest 8 shown.

Attention rank: #307 of 355 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 221 days after the earliest competitor.

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