AI · alternatives · 2026
24 alternatives to ModelRed
Hi everyone, We built ModelRed to test AI models and apps for security issues. Ran 4,182 attack probes against 9 leading models to see what would break. Leaderboard: https://modelred.ai (no signup, just check it out) Claude scored 9.5/10 but still failed on medical/financial prompts. Mistral Large scored 3.3/10. The gap between best and worst is huge. We test for prompt injections, data leaks, jailbreaks, risky tool calls, domain specific hacks, basically everything that goes wrong when your LLM has access to real data and APIs. The platform runs these tests…
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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Hi all, I built a backdoored LLM to demonstrate how open-source AI models can be subtly modified to include malicious behaviors while appearing completely normal. The model, "BadSeek", is a modified version of Qwen2.5 that injects specific malicious code when certain conditions are met, while behaving identically to the base model in all other cases. A live demo is linked above. There's an in-depth blog post at https://blog.sshh.io/p/how-to-backdoor-large-language-models. The code is at https://github.com/sshh12/llm_backdoor The interesting technical…
2025 · sshh12--llm-backdoor.modal.run · its alternatives →
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Opper AI▲229Hey HN! After the Car Wash Test post got quite a big discussion going (400+ comments, https://news.ycombinator.com/item?id=47128138), I spent the past few weeks building a tool so anyone can run these kinds of questions and get structured results. No signup and free to use. You type a question, define answer options, pick up to 50 models at a time from a pool of 200+, and they all answer independently under identical conditions. No system prompt, structured output, same setup for every model. You can also run a debate round where models see each other's reasoning and get a…
Jul 2026 · opper.ai · its alternatives →
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Fabraix▲196We built Adversarial Cost to Exploit (ACE), a benchmark that measures the token expenditure an autonomous adversary must invest to breach an LLM agent. Instead of binary pass/fail, ACE quantifies adversarial effort in dollars, enabling game-theoretic analysis of when an attack is economically rational. We tested six budget-tier models (Gemini Flash-Lite, DeepSeek v3.2, Mistral Small 4, Grok 4.1 Fast, GPT-5.4 Nano, Claude Haiku 4.5) with identical agent configs and an autonomous red-teaming attacker. Haiku 4.5 was an order of magnitude harder to break than every other model; $10.21 mean…
May 2026 · fabraix.com · its alternatives →
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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 →
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Anthropic and OpenAI's publicly available models are explicitly guard-railed so that they refuse offensive tasks. And their cyber-focussed models are gated for enterprises. This leaves SMEs and mid market open to major vulnerabilities. AI can be used as both an adversarial and defensive tool in the world of cyber. A worst case outcome is if only the adversaries have access. Meanwhile, most existing AI cyber tools are just wrappers. The problem is that they still have all the guardrails on from the foundation model where they will inherit its refusals. For this project we've post-trained a…
Jun 2026 · argusred.com · its alternatives →
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The Only AI Tool That Doesn't Trust AI
Mar 2026 · triall.ai · its alternatives →
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I'm Vivek, co-founder/CEO of HackerRank (YC S11); You may know us as a hiring tool for developers/companies. Over the years, we have built up deep expertise in generating programming challenges, and we are now using that to make coding models better. Our first launch is Model Kombat -- an arena where you can directly compare anonymized coding models, side by side, on real problems. * Pick an arena (Java, Python, etc.) * Each battle has 3 rounds: see the problem + two model outputs -> vote on which you’d actually prefer * Leaderboards + problem statements are updated weekly. We…
2025 · astra.hackerrank.com · its alternatives →
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Ithy AI▲167This is another one of my automate-my-life projects - I'm constantly asking the same question to different AIs since there's always the hope of getting a better answer somewhere else. Maybe ChatGPT's answer is too short, so I ask Perplexity. But I realize that's hallucinated, so I try Gemini. That answer sounds right, but I cross-reference with Claude just to make sure. This doesn't really apply to math/coding (where o1 or Gemini can probably one-shot an excellent response), but more to online search, where information is more fluid and there's no "right" search engine + text…
2025 · ithy.com · its alternatives →
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Redteaming LLMs using other LLMs. Contribute to traghav/auto-redteam development by creating an account on GitHub.
2023 · github.com · its alternatives →
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Compare AI models side-by-side on same prompt
Feb 2026 · testaimodels.com · its alternatives →
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thisorthis.ai▲135Hey HN — I'm Parth, I built thisorthis.ai because I was tired of copy-pasting the same prompt across ChatGPT, Claude, and Gemini tabs to figure out which model actually gave the best answer. What it does: You type one prompt, pick 2–6 models (we support 47 text models and several image models across OpenAI, Anthropic, Google, xAI, Meta, Amazon, Mistral, Cohere, AI21), and see every response side-by-side. There's also a feature called SmartPick that uses an LLM evaluator to score each response on Clarity, Accuracy, Completeness, and Helpfulness — useful when you're comparing 6 models and…
2024 · thisorthis.ai · its alternatives →
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Trails▲81Hey all, Justin here. I previously built Phind, the AI search engine for developers. One of the biggest problems we had there was figuring out what went wrong with bad searches. We had tons of searches per day, but less than 1% of users gave any explicit feedback. So we were either manually digging through searches or making general system improvements and hoping they helped. This problem gets harder with agents. Traces are longer and more complex. It takes more effort to review them, so I'm building a tool that lets you analyze LLM outputs directly to help developers of LLM apps and agents…
Jan 2026 · trails-red.vercel.app · its alternatives →
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Lovelaice▲10Multi-model AI testing, evaluation, optimization made simple
2025 · lovelaice.com · its alternatives →
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Spec27▲34Hi HN! We’re a team of ML validation specialists and we’ve been building /Spec27, a tool for testing whether AI agents still do their job safely and reliably as models, prompts, tools, and surrounding systems change. We started working on this because a lot of current LLM evaluation work seems aimed at scoring general model behavior, while many teams are deploying systems that have a specific mission to fulfill. Many of the tools also assume you have full access to the agent stack and traces so you can place SDKs and Gateways, but a lot of agents are being created on vendor platforms…
Apr 2026 · spec27.ai · its alternatives →
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Hey HN, We’re two developers (co-founders) with a team of 20 who got tired of spending hours reviewing PRs, so we built Infinitcode.ai, an AI-powered code reviewer that: - *Summarizes PRs in plain English*: No more deciphering 1,000-line diff jungles - *Catches more than bugs*: Security holes, performance pitfalls, code smells, even typos (yes, we’ll flag “vurnerabilities” and vulnerabilities) - *Zero onboarding*: Works instantly—no “let me learn your codebase for weeks” nonsense. Why we’re posting: We’re in alpha and need brutal honesty. Roast our tool, mock our UI, or tell us why AI will…
2025 · infinitcode.ai · its alternatives →
- 17
Hi HN, I built this open-source LLM red teaming tool based on my experience scaling LLMs at a big co to millions of users... and seeing all the bad things people did. How it works: - Uses an unaligned model to create toxic inputs - Runs these inputs through your app using different techniques: raw, prompt injection, and a chain-of-thought jailbreak that tries to re-frame the request to trick the LLM. - Probes a bunch of other failure cases (e.g. will your customer support bot recommend a competitor? Does it think it can process a refund when it can't? Will it leak your user's address?) -…
2024 · promptfoo.dev · its alternatives →
- 18TS
Hello Hacker News community! I'm currently working in financial risk management within the banking sector, and I began my career as a Data Science specialist. For quite some time, my friend and I have been developing a small pet project just for fun. This tool has repeatedly helped us save time when testing various hypotheses and machine learning models. The core idea is to combine different scripts—created in various programming languages and virtual environments—within a minimalist graphical interface. Whether you're building models, running a local neural network, or sending requests to…
2024 · its alternatives →
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Oumi▲24Since yesterday, I've created a dataset out of a few docs I had (hackathon organization instructions) and then started fine tuning qwen 3.5. So it only took a few hours! I'm impressed by the ease of use - it's a chatbot and even if you don't have a lot of experience you can follow steps. Though don't want to undermine it, I'm sure could be a great fit for serious labs too.
Apr 2026 · oumi.ai · its alternatives →
- 21
Find vulnerabilities in your AI prompts before your users do
Aug 2026 · testmyprompt.net · its alternatives →
- 22
Hey HN - I built ModelGuessr, a game where you chat with a random AI model and try to guess which one it is. A big open question in AI is whether there's enough brand differentiation for AI companies to capture real profits. Will models end up commoditized like cloud compute, or differentiated like smartphones? I built ModelGuessr to test this. I think that people will struggle more than they expect. And the more model mix-ups there are, the more commodity-like these models probably are. If enough people play, I'll publish some follow-up analyses on confusion patterns (which models get…
Dec 2025 · model-guessr.com · its alternatives →
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Find AI vulnerabilities before hackers do
Mar 2026 · promptbrake.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 →