AI · alternatives · 2026
24 alternatives to LLM Debate Benchmark
Adversarial multi-turn benchmark for LLM debate quality, using side-swapped matchups and multi-model judging to rank models by judged debate performance. - lechmazur/debate
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1

I found that duplicating a specific block of 7 middle layers in Qwen2-72B, without modifying any weights, improved performance across all Open LLM Leaderboard benchmarks and took #1. As of 2026, the top 4 models on that leaderboard are still descendants. The weird finding: single-layer duplication does nothing. Too few layers, nothing. Too many, it gets worse. Only circuit-sized blocks of ~7 layers work. This suggests pretraining carves out discrete functional circuits in the layer stack that only work when preserved whole. The whole thing was developed on 2x RTX 4090s in my basement. I'm…
Mar 2026 · dnhkng.github.io · its alternatives →
- 2
LLM Stats▲293I was overspending on GPT-4o. It was really hard to compare different models I could switch to, so I built this LLM comparison tool. It shows leaderboards, pricing, and performance data across 100+ LLMs (including all major providers and open-source models). Key features: - Live pricing comparisons - Benchmark Scores (MMLU, HumanEval, GPQA, etc.) - Context length vs cost analysis - Speed/throughput tests across providers - Quality vs price visualizations - Open source (all data verifiable) Try it out: https://llmstats.com I'd like to know your opinion :) Tech stack: Next.js,…
Oct 2025 · llm-stats.com · its alternatives →
- 3

Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly. - Andyyyy64/whichllm
May 2026 · github.com · its alternatives →
- 4

I replicated David Ng's RYS method (https://dnhkng.github.io/posts/rys/) on consumer AMD GPUs (RX 7900 XT + RX 6950 XT) and found something I didn't expect. Transformers appear to have discrete "reasoning circuits" — contiguous blocks of 3-4 layers that act as indivisible cognitive units. Duplicate the right block and the model runs its reasoning pipeline twice. No weights change. No training. The model just thinks longer. The results on standard benchmarks (lm-evaluation-harness, n=50): Devstral-24B, layers 12-14 duplicated once: - BBH Logical Deduction: 0.22 → 0.76…
Mar 2026 · github.com · its alternatives →
- 5

Ever wish you could get the best arguments for both sides of a debate? I built an AI-powered debate platform that pits language models against each other on controversial topics. Each AI is randomly assigned a side (pro/con). You vote before and after to see if you were persuaded. Most content today presents lopsided arguments. They provide strong points for one side, weak ones for the other. This project aims to surface the strongest arguments from both sides, using LLMs to simulate a fair debate. With enough usage, I want to use it to benchmark LLMs. My hypothesis is that randomly…
Nov 2025 · aidebatearena.app · its alternatives →
- 6

Create debates between different personas with any LLM
2024 · its alternatives →
- 7IM
Got tired of my debates with my friend's ending in "I'm right bc I said so" so I made a platform where you can debate with your friend's(or a bot, recently added feature) about whatever you want, and after the debate is done a LLM judges who's more sound in logic. Gain points and climb the leaderboard! Feedback and criticism would be appreciated(there's a discord in there if you wanna talk more in depth) p.s.: I decided to use google acc sign in since it makes the whole thing easier to manage(live chatroom feature, etc.). I don't actually do anything with your emails
2025 · crs-prod-rankeddebate-l4dnggfaca-nn.a.run.app · its alternatives →
- 8
Deepmark AI▲97LLM benchmarking tool for task-specific metrics on your data
2023 · github.com · its alternatives →
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Hi HN community! I am excited to share my recently upgraded website, DebateDevil (https://debate-devil.com), an AI chat platform designed to help users practice debates, challenge their ideas, and expand their thinking. I created this site to provide a more objective opinion and help users consider their hypotheses from multiple perspectives. example discussin: ``` AI: The time has come to test your hypothesis and beliefs. I will argue against any topic. What do you want to debate? You: AI will take away most jobs from humans. AI: I understand your concern about AI taking away jobs…
2023 · debate-devil.com · its alternatives →
- 11

Benchmark evaluating LLMs on their ability to create and resist disinformation. Includes comprehensive testing across major models (Claude, GPT-4, Gemini, Llama, etc.) with standardized evaluation metrics. - lechmazur/deception
2024 · github.com · its alternatives →
- 12

Hi HN community, I have been working on benchmarking publicly available LLMs these past couple of weeks. More precisely, I am interested on the finetuning piece since a lot of businesses are starting to entertain the idea of self-hosting LLMs trained on their proprietary data rather than relying on third party APIs. To this point, I am tracking the following 4 pillars of evaluation that businesses are typically look into: - Performance - Time to train an LLM - Cost to train an LLM - Inference (throughput / latency / cost per token) For each LLM, my aim is to benchmark them for…
2023 · github.com · its alternatives →
- 13
DebatoMate▲100Your self-hostable AI debate companion
2023 · squidandfish.gumroad.com · its alternatives →
- 14

- 15

Test LLM prompts & models side-by-side against many inputs
2024 · its alternatives →
- 16AT
I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com · its alternatives →
- 17

Test and compare results from Large Language Models (LLMs) simultaneously, including Anthropic's Claude 1.2, OpenAI's GPT-4, GPT-3.5 turbo, and Cohere's CommandXL Nightly. Analyze the results side-by-side in a single UI on top of LLM APIs.
2023 · retool.com · its alternatives →
- 18

What counts as rigorous academic argument?
2016 · radiolab.org · its alternatives →
- 19PP
I've been working on applying LLMs to long-context, verifiable problems over the past year, and today I'm releasing a benchmark of 62,000 pencil puzzles across 94 types (sudoku, nonori, slitherlink, etc.). The benchmark also allows for intermediate checks /rule breaks for all varieties at any step. I tested 51 models against a subset (300 puzzles) in two modes: single-shot (output the full solution) and agentic (iterate with verifier feedback). Some results: - Best model (GPT 5.2@xhigh) solves 56%. (~ half the puzzles are unsolved by any model) - Agentic solves average 29 turns. The…
Mar 2026 · ppbench.com · its alternatives →
- 20

Hello HN! I was fed up switching between multiple UIs to ask GPT, Claude, etc… the same question and comparing the answers. So I built a way to ask multiple models the same question efficiently by having the LLM compare the responses and only show you new and valuable information from the 2nd model. This way you still get a fast response as normal from the 1st model, but also get any added value provided by the 2nd model. Initially I built my own UI to use this, but stumbled upon Open WebUI (formerly Ollama WebUI) which is fantastic, but is made more for local access to LLMs. So I talked to…
2025 · polychat.co · its alternatives →
- 21
debatly▲4AI debate analysis with speaker tracking and fact checks
Jun 2026 · debatly.online · its alternatives →
- 22CL
2023 · convoclash.net · its alternatives →
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Thematic Generalization Benchmark: measures how effectively various LLMs can infer a narrow or specific "theme" (category/rule) from a small set of examples and anti-examples, then detect which item truly fits that theme among a collection of misleading candidates. - lechmazur/generalization
2025 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →