Life & fun · alternatives · 2026
24 alternatives to How clanker are you? A reverse Turing test
You write 8 text completions and open models score how predictable each word was too them. Predictable => clanker. You can share results with your friends. The scoring checks every word you write against the model's logprobs. Right now I'm using Llama3.1, Deepseek v3 and Qwen3 to keep costs low. I tried to calibrate it so other models (chatgpt/claude) score 100% and interesting human responses score in the 10-30% range. Totally free, no signup
How clanker are you?" is a reverse Turing test that measures how predictable your writing is. Users complete eight text prompts, and the tool scores each word against language models' probability distributions—lower… 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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ClankerPass▲78Can you convince an AI that you're an AI?
Apr 2026 · clankerpass.com · its alternatives →
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I spent a lot of time and money on this rather big side project of mine that attempts to replicate the mechanistic interpretability research on proprietary LLMs that was quite popular this year and produced great research papers by Anthropic [1], OpenAI [2] and Deepmind [3]. I am quite proud of this project and since I consider myself the target audience for HackerNews did I think that maybe some of you would appreciate this open research replication as well. Happy to answer any questions or face any feedback. Cheers [1]…
2024 · github.com · its alternatives →
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With more traffic moving off-web and into LLMs, I got curious about what traces we leave "in the weights". My design partner and I built a site in the past few weeks that checks recognition across frontier and small models. It queries many of them in parallel, clusters the responses, and tells you how strongly they recognize you. Happy to answer any questions here!
Jun 2026 · intheweights.com · its alternatives →
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Tinkerer Club▲501The private club for ppl who automate, self-host, and use AI
Feb 2026 · tinkerer.club · its alternatives →
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Test your HN title against a neural network. Contribute to victorqribeiro/hntitlenator development by creating an account on GitHub.
2019 · github.com · its alternatives →
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A fun project that I built to try out R1 Distill Llama 70B. Enjoy :)
2025 · hn-wrapped.kadoa.com · its alternatives →
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Hey Folks! I've been building an open source benchmark for measuring local LLM performance on your own hardware. The benchmarking tool is a CLI written on top of Llamafile to allow for portability across different hardware setups and operating systems. The website is a database of results from the benchmark, allowing you to explore the performance of different models and hardware configurations. Please give it a try! Any feedback and contribution is much appreciated. I'd love for this to serve as a helpful resource for the local AI community. For more check out: - Website:…
2025 · localscore.ai · its alternatives →
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A Wordle decoder that guesses your guesses. Contribute to mattruzicka/wordle_decoder development by creating an account on GitHub.
2022 · github.com · its alternatives →
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A bot written in Scala 3 to stress test text-based MMORPGs (MUDs). - ryanberckmans/noric-bot
2019 · github.com · its alternatives →
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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 →
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Copy PR comments into clanker-ready prompts
Jun 2026 · pleasefixclanker.com · 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 →
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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 →
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Hi HN, I have been working on this website for a few weeks with some buddies of mine and would love if you checked it out. TuringJest provides a jackbox-esque experience with its two game modes. *One Shot Prompt* - Submit a prompt for all players (including the AI) to answer. - Answer your prompts in the way that you think ChatGPT would answer them. - Vote for who you think the real AI is. *Talk It Out* - Plan an event in a group chat with your friends. - Trick everyone into thinking you are the AI while voting for the real AI. Let me know what you think!
2023 · turingjest.app · its alternatives →
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Spelltest framework simulates conversations between AI ‘synthetic users' in an environment to test and refine LLM-based applications. It ensures your app converse with utmost accuracy and relevance. Post-chat, Spelltest assesses responses, providing qualitative and quantitative feedback on performance. Suitable for both chat and completion modes. When to use: - After modifying your prompt. - When your LLM provider updates. - As a CI step for you repo. All feedback and collaborations appreciated!
2023 · github.com · its alternatives →
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Deepmark AI enables a unique testing environment for language models (LLM) assessment on task-specific metrics and on your own data so your GenAI-powered solution has predictable and reliable performance. - IngestAI/deepmark
2023 · github.com · its alternatives →
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Hey HN, I’m a dev and a dad to a 10-year-old. I built this because I caught my daughter using ChatGPT to do her history homework. She wasn't learning; she was just acting as a "middleware" between the AI and the paper. The Backstory: I realized the problem isn't the AI—it's the zero-friction answers. Most "AI for kids" apps are just "parrots"—they mimic intelligence by repeating patterns. What’s Different: Qurio is a "Bicycle" for the mind. It treats the child like a future "Architect" rather than a "Junior Executor." Technically, it wraps an LLM in a strict "Socratic Loop." It detects…
Feb 2026 · thinkqurio.com · its alternatives →
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I've been tinkering with getting Llama-8B to bootstrap its own research skills through self-play. The model generates questions about documents, searches for answers, and then learns from its own successes/failures through RL (hacked up Unsloth's GRPO code). Started with just 23% accuracy on Apollo 13 mission report questions and hit 53% after less than an hour of training. Everything runs locally using open-source models. It's cool to see the model go from completely botching search queries to iteratively researching to get the right answer.
2025 · github.com · its alternatives →
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Unleash AI personas on your product and get real UX feedback in minutes. No scheduling, no waiting, no guessing.
Apr 2026 · clankerview.com · its alternatives →
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G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com · its alternatives →
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I built a small game that tests your ability to differentiate between human written text and large language models. Each round shows two similar sentences, one is drawn from a 40‑k sentence human‑written dataset (with citations) and the other generated by an AI model. It’s a lightweight way to build some AI literacy and see how tricky it can be to tell real writing from synthetic text.
2025 · ai-or-human.com · its alternatives →
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I’ve been building a crowd-sourced AI detection benchmark. Two responses to the same prompt — one from a real human (pre-2022, provably pre prevalence of AI slop on the internet), one generated by AI. You pick the slop. Three wrong and you’re out. The dataset: 16K human posts from Reddit, Hacker News, and Yelp, each paired with AI generations from 6 models across two providers (Anthropic and OpenAI) at three capability tiers. Same prompt, length-matched, no adversarial coaching — just the model’s natural voice with platform context. Every vote is logged with model, tier, source, response…
Mar 2026 · slop-or-not.space · its alternatives →
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