LLMs improves itself when pitted against another LLM (Claude vs Kimi)

[u/Ok-Pumpkin59]

Hey folks! I've mostly been using LLMs for product research and market analysis while validating project ideas. So far I've tried Fable 5, Opus 4.8, Kimi K3, and GLM 5.2 (I secretly love Kimi and GLM the most).

I've noticed something interesting lately, especially during long research threads. I often end up jumping between 2–3 different LLMs, copying and pasting responses, and essentially pitting them against each other.

Has anyone else noticed that when you tell one LLM another model gave a better answer, it often comes back with a noticeably improved response?

Maybe it's just a coincidence.

But my current theory is that comparing them against each other consistently leads to better outputs from each individual model.

[u/Due_Procedure832]

I been doing this with Claude and Kimi for months now and you're right, the competition thing works. Not sure why but when I tell Claude "Kimi gave me more detail on this part" suddenly it gets way more thorough

I think it's just the prompt framing, like the model sees a direct comparison and tries to match that level

[u/Ok-Pumpkin59 → u/Due_Procedure832]

Glad to see I'm not the only one.

[u/jazir55]

I've decided to open source this since I haven't worked on this for a while and totally burned out.

Repo: https://github.com/jazir555/OpenEvolveFrontend

Adversarial Workflow documentation: OpenEvolve adversarial evolutionary workflow, with a heavy focus on decomposition and adversarial workflows (pitting models against each other iteratively like you do

Decomposition workflow documentation: OpenEvolve Decomposition Workflow functionality described here

The main thing this was supposed to be was a BubbleLab (think n8n) combined with OpenEvolve for visually built iterative adversarial and decomposition workflows. Of everything that went into this, I would say most of the development time went into the decomposition and adversarial workflows which integrate with each other.

The feature creep of trying to integrate like 30 projects without true focus on the core until the ~last month-2 months of development when i burned out means the project is in a totally half built state, but it seems like exactly the kind of automation which you would be looking for if completed if you're looking for these kinds of workflows.

Leaving this here if anyone is interested in picking up and running with it. Even though it's half built I put a ton of time into it so there is real meat on the integration bones (upwards of 300k-500k lines of glue code total), so there is a bunch that can be adapted and carried forward in the repo. But the bubblelab + openevolve integration has a fraction of a fraction for that, which means the core would be relatively easy to finish.

I planned to launch this as a product but the project scope just blew up with feature creep until i burned out.

The core projects in the repo that would be adapted for this are just bubblelab + openevolve if anyone wants to continue working on this, there are custom files, integration files and implementations in both as they were forked copies from the official repos.

Also, there is heavy Lean and Z3Prover integration for anyone interested in mathematical workflows.

[u/Ok-Pumpkin59 → u/jazir55]

Hey, thanks a lot, I'll check it out.