llm-circuit-finder

AI

llm layer duplication

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llm-circuit-finder

Duplicate 3 layers in a 24B LLM, logical deduction .22→.76. No training

github.com

#llm layer duplication#reasoning circuits#transformer layers#lm-eval benchmarks

265points
80comments
#176of 4,366 in 2026
Top 5%of 2026 by points

How HN took it

CuriousMostly questions and neutral comments

5 positive, 27 neutral or asking, 0 mixed, 9 critical, out of 41 comments about the project. Thread score -0.12.

Idea: 4 for, 5 againstPerformance: 0 for, 4 against

The thread, comment by comment

Each row is a top-level comment and its replies, in HN's order. Select a cell to open that comment on HN.

positive neutral or mixed critical about another commenter or something else the maker

What HN said

What people liked

  • Interesting, cool result on the logical deduction benchmark

    From 2 comments
    • This is very cool
      edg5000 on HN
    • There's still a lot of low hanging fruit left IMO. Good find and rather funny to think about as you can have someone simply clone the various layers multiple times and instead of…
      nowittyusername on HN
  • Fits with pruning findings that middle layers carry reasoning

    From 1 comment
    • this lines up with what pruning papers have been finding, the middle layers carry most of the reasoning weight and you can often drop the outer ones without much loss. cool to…
      zhangchen on HN

Objections

  • Prior art: David Ng's RYS method and earlier layer duplication work

    From 3 comments
    • > I replicated David Ng's RYS method [...] found something I didn't expect. > Transformers appear to have discrete "reasoning circuits" — contiguous blocks of 3-4 layers that act…
      simgt on HN
    • Wow, every single word in the original post and on that README.md is pure LLM. How sad. In any case, this has been done at least since the very first public releases of Llama by…
      Karuma on HN
    • The method used here by David Ng, was discussed a few days ago at https://news.ycombinator.com/item?id=47322887
      kristianp on HN
  • Gains may be benchmark noise or come with losses on other tasks

    From 3 comments
    • But if it got worse on other tests, it doesn't do much good, right?
      XCSme on HN
    • What, just randomly choose some "layer" and duplicate it and give some arbitrary reasoning went from 0.2 -> 0.7, i don't know man. You need to use real benchmarks.
      m3kw9 on HN
    • I’d love to believe this is real, but I’m pretty sure you will lose performance on a “fair” mix of tasks, even after fine tuning. I know multiple teams have explored recurrent…
      rao-v on HN
  • Small test sample (50 per task) and speed-limited validation

    From 1 comment
    • I published the results for devstral... results folder of the github https://github.com/alainnothere/llm-circuit-finder/tree/main/results I'm using the following configuration…
      xlayn on HN
  • Post and README appear LLM-written

    From 1 comment
    • Wow, every single word in the original post and on that README.md is pure LLM. How sad. In any case, this has been done at least since the very first public releases of Llama by…
      Karuma on HN

Requests

  • Publish per-task benchmark results

    From 1 comment
    • Would you be able to publish the individual benchmarks for Qwen2.5-Coder-32B? GSM8K specifically would be useful to look at.
      colejhudson on HN
  • Test on newer Qwen models

    From 1 comment
    • Why test on Qwen 2.5 when Qwen 3 has been out for about a year, and Qwen 3.5 for a month? My problem with this is ironically entirely vibes based, that for some reason, LLMs love…
      christianqchung on HN
  • Try skipping layers instead of duplicating them

    From 1 comment
    • That's interesting, could you point me to some source on these findings? It seems to me that the difference between "iterative improvement" as you put it and "close to the…
      4bpp on HN

Questions

  • Why the logical deduction gain happens and whether it generalises

    From 2 comments
    • Assuming the benchmarks are sound (rather than capturing a fluke), the provided explanation still does not pass the smell test. As far as I can tell, there is nothing about the…
      4bpp on HN
    • the "reasoning circuits" framing is doing a lot of work here. tidy story, fits the result, but I'm not sure it explains anything - you duplicated layers and got better scores,…
      the_harpia_io on HN
  • How to run these models on AMD GPUs

    From 1 comment

Alternatives named

  • David Ng's RYS method

    From 1 comment
    • > I replicated David Ng's RYS method [...] found something I didn't expect. > Transformers appear to have discrete "reasoning circuits" — contiguous blocks of 3-4 layers that act…
      simgt on HN
  • Depth Up-Scaling (Solar 10.7B)

    From 1 comment
    • Reminds me of Solar 10.7B, which was a very good model for its size ~2 year ago and the "Depth Up-Scaling" technique behind it. Although, that involved continued training after…
      woadwarrior01 on HN
  • Layer pruning

    From 1 comment
    • you can also have removed layers of models and keep the same score in benchmarks [1]. i feel that sometimes a lot of the layers might just be redundant and are not fully needed…
      snats on HN

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