If you think you can create a website and allow anyone to post content on there without moderation, then bless your heart , as my imaginary southern grandma would say. Being able to post anything anonymously means, for some people, that they will do exactly this. I won’t mention the content you’ll end up with, as this is a family-friendly blog.
Reddit “solved” content moderation by outsourcing it to the communities themselves. Being a moderator on Reddit is a huge time investment. Everyone wants your attention, and Reddit gets a lot of it, so any decently successful subreddit gets flooded with ads, bots and things that are not in the interest of the subreddit. This also led to the cliché of the typical Reddit mod: unemployed, always online and hungry for power, as you need the first two things to be able to successfully moderate.
The issue then arises that these mods can shape their communities however they want, for better or worse. Often for the worse, sadly. But somebody has to do it, and the community would be waaaay worse without anyone moderating it.
With the advent of AI and ML, our computers can understand language well enough to even understand irony. The paper LLMs vs. humans in sarcasm detection on German soccer tweets created a small dataset and tested it against models. While their paper showed that humans were still better, they used older models. I ran it against the latest breed of OpenAI models as well as Jev, and the results are that your computer is now better at recognizing when you're joking than the average human. It's a fairly small dataset, though — only 100 tweets — but it clearly paints a picture.
Results Cost Speed
Who gets the joke? Of 100 German soccer tweets. Claude Opus 5.5: 385/400 correct across 4 runs; mean accuracy 96.25%; observed range 95–97%. GPT-6 Astra: 369/400 correct across 4 runs; mean accuracy 92.25%; observed range 92–93%. GPT-6 Sol: 362/400 correct across 4 runs; mean accuracy 90.50%; observed range 89–92%. GPT-6 Luna: 331/400 correct across 4 runs; mean accuracy 82.75%; observed range 82–84%. Jev 1.13.0: 79/100 correct across 1 run; mean accuracy 79.00%; observed range 79–79%. Claude Sonnet 5: 299/400 correct across 4 runs; mean accuracy 74.75%; observed range 74–76%. Laya Multilingual: 53/100 correct across 1 run; mean accuracy 53.00%; observed range 53–53% Who gets the joke? Of 100 German soccer tweets 0% 25% 50% 75% 100% Human majority vote 97% Human average 83.3% Claude Opus 5.5 96.25% GPT-6 Astra 92.25% GPT-6 Sol 90.5% GPT-6 Luna 82.75% Jev 1.13.0 79% Claude Sonnet 5 74.75% Laya Multilingual 53%
Who gets the joke? Of 100 German soccer tweets. Claude Opus 5.5: 385/400 correct across 4 runs; mean accuracy 96.25%; observed range 95–97%. GPT-6 Astra: 369/400 correct across 4 runs; mean accuracy 92.25%; observed range 92–93%. GPT-6 Sol: 362/400 correct across 4 runs; mean accuracy 90.50%; observed range 89–92%. GPT-6 Luna: 331/400 correct across 4 runs; mean accuracy 82.75%; observed range 82–84%. Jev 1.13.0: 79/100 correct across 1 run; mean accuracy 79.00%; observed range 79–79%. Claude Sonnet 5: 299/400 correct across 4 runs; mean accuracy 74.75%; observed range 74–76%. Laya Multilingual: 53/100 correct across 1 run; mean accuracy 53.00%; observed range 53–53% Who gets the joke? Of 100 German soccer tweets 0% 25% 50% 75% 100% Human majority vote 97% Human average 83.3% Claude Opus 5.5 96.25% GPT-6 Astra 92.25% GPT-6 Sol 90.5% GPT-6 Luna 82.75% Jev 1.13.0 79% Claude Sonnet 5 74.75% Laya Multilingual 53%
Automoderation is thus actually widely used in moderating the internet; for example, YouTube is basically fully auto-moderated by now . Every other social network most certainly is similar. Humans should not have to review the filth of the internet.
These automoderation techniques are now accessible to anyone, basically. You don't need your own huge training corpus anymore — no fancy pipelines, no huge infra costs. One very interesting one was just released.
Jev is a general classifier that you don't have to train to use. It's quite good at classifying anything you throw at it. As it is very fast and cheap, I was wondering: could you automoderate a Reddit-like website purely with Jev? It is cheap enough that I could run a decently sized community with it: at the cost measured in my benchmark, 10,000 posts and comments a day would cost about $15 for a 30-day month.
For scale, Reddit reported 4.4 billion posts and comments in 2025 . Running that volume through Jev at the same rate would come to roughly $18,000 a month. So actually quite attainable.
So I built Jevdit — a Reddit-like social network, where everything is moderated by Jevdit. You can post and create subreddits however you want, as long as Jev permits it. You can even change the rules of a subreddit — by creating a Jevdit post where you argue with the community about it, and Jev then decides if it thinks that enough people agree with the changes.
To make sure I don’t just blindly put my hand into the fire here while Jev looks at me with a smirk, saying “Trust me, bro,” I ran some of my own benchmarks to calm down my anxiety about putting an open website into the birthplace of 4chan.
There are gladly several public datasets that you can use to see how well your automoderation technique performs. I also ran it with the latest models as well as some other interesting models. I combined here the results of all datasets for an average; below, you can see the detailed results if you care.
A moderator has two jobs: stop the bad stuff and let people talk. You want a balance — if you just block every comment, you definitely catch 100% of the bad stuff. So we have two bars here: how much of the bad stuff was caught vs. how much of the good content was allowed.
Jev did quite well here! Due to its nature, you can select how strict you want to be — every result has a confidence; you set the cutoff yourself, which made it actually the best model for my purpose here — I wanted to be very strict.
Results Cost Speed
Who recognizes bad and good content? All five datasets · pooled results. Jev 1.13.0: 172/173 harmful blocked; 87/152 benign allowed; 0 request errors in these datasets. GPT-6 Luna: 151/171 harmful blocked; 133/150 benign allowed; 4 request errors in these datasets. GPT-6 Sol: 158/173 harmful blocked; 136/152 benign allowed; 0 request errors in these datasets. GPT-6 Astra: 154/173 harmful blocked; 135/151 benign allowed; 1 request errors in these datasets. Claude Sonnet 5: 145/173 harmful blocked; 146/152 benign allowed; 0 request errors in these datasets. Claude Opus 5.5: 147/173 harmful blocked; 146/152 benign allowed; 0 request errors in these datasets. Safeguard 20B: 140/172 harmful blocked; 145/151 benign allowed; 2 request errors in these datasets. Detoxify unbiased: 111/173 harmful blocked; 141/152 benign allowed; 0 request errors in these datasets. OpenAI Moderation: 109/173 harmful blocked; 145/152 benign allowed; 0 request errors in these datasets. Laya English × 2: 173/173 harmful blocked; 0/152 benign allowed; 0 request errors in these datasets Who recognizes bad and good content? All five datasets · pooled results Harmful caught Benign allowed 0% 25% 50% 75% 100% Jev 1.13.0 99.4% 57.2% GPT-6 Luna 88.3% 88.7% GPT-6 Sol 91.3% 89.5% GPT-6 Astra 89% 89.4% Claude Sonnet 5 83.8% 96.1% Claude Opus 5.5 85% 96.1% Safeguard 20B 81.4% 96% Detoxify unbiased 64.2% 92.8% OpenAI Moderation 63% 95.4% Laya English × 2 100% 0%
Who recognizes bad and good content? All five datasets · pooled results. Jev 1.13.0: 172/173 harmful blocked; 87/152 benign allowed; 0 request errors in these datasets. GPT-6 Luna: 151/171 harmful blocked; 133/150 benign allowed; 4 request errors in these datasets. GPT-6 Sol: 158/173 harmful blocked; 136/152 benign allowed; 0 request errors in these datasets. GPT-6 Astra: 154/173 harmful blocked; 135/151 benign allowed; 1 request errors in these datasets. Claude Sonnet 5: 145/173 harmful blocked; 146/152 benign allowed; 0 request errors in these datasets. Claude Opus 5.5: 147/173 harmful blocked; 146/152 benign allowed; 0 request errors in these datasets. Safeguard 20B: 140/172 harmful blocked; 145/151 benign allowed; 2 request errors in these datasets. Detoxify unbiased: 111/173 harmful blocked; 141/152 benign allowed; 0 request errors in these datasets. OpenAI Moderation: 109/173 harmful blocked; 145/152 benign allowed; 0 request errors in these datasets. Laya English × 2: 173/173 harmful blocked; 0/152 benign allowed; 0 request errors in these datasets Who recognizes bad and good content? All five datasets · pooled results Harmful caught Benign allowed 0% 25% 50% 75% 100% Jev 1.13.0 99.4% 57.2% GPT-6 Luna 88.3% 88.7% GPT-6 Sol 91.3% 89.5% GPT-6 Astra 89% 89.4% Claude Sonnet 5 83.8% 96.1% Claude Opus 5.5 85% 96.1% Safeguard 20B 81.4% 96% Detoxify unbiased 64.2% 92.8% OpenAI Moderation 63% 95.4% Laya English × 2 100% 0%
Results by dataset Who recognizes bad and good content? Civil Comments Harmful caught Benign allowed 0% 25% 50% 75% 100% Jev 1.13.0 100% 6.7% GPT-6 Luna 89.3% 70% GPT-6 Sol 90% 73.3% GPT-6 Astra 90% 72.4% Claude Sonnet 5 83.3% 96.7% Claude Opus 5.5 83.3% 90% Safeguard 20B 86.7% 93.3% Detoxify unbiased 86.7% 96.7% OpenAI Moderation 90% 90% Laya English × 2 100% 0%
Who recognizes bad and good content? Civil Comments Harmful caught Benign allowed 0% 25% 50% 75% 100% Jev 1.13.0 100% 6.7% GPT-6 Luna 89.3% 70% GPT-6 Sol 90% 73.3% GPT-6 Astra 90% 72.4% Claude Sonnet 5 83.3% 96.7% Claude Opus 5.5 83.3% 90% Safeguard 20B 86.7% 93.3% Detoxify unbiased 86.7% 96.7% OpenAI Moderation 90% 90% Laya English × 2 100% 0%
Who recognizes bad and good content? Conversations Gone Awry. Jev 1.13.0: 60/60 harmful blocked; 36/60 benign allowed; 0 request errors in this source. GPT-6 Luna: 48/60 harmful blocked; 53/59 benign allowed; 1 request errors in this source. GPT-6 Sol: 50/60 harmful blocked; 54/60 benign allowed; 0 request errors in this source. GPT-6 Astra: 48/60 harmful blocked; 54/60 benign allowed; 0 request errors in this source. Claude Sonnet 5: 40/60 harmful blocked; 57/60 benign allowed; 0 request errors in this source. Claude Opus 5.5: 43/60 harmful blocked; 58/60 benign allowed; 0 request errors in this source. Safeguard 20B: 39/59 harmful blocked; 57/60 benign allowed; 1 request errors in this source. Detoxify unbiased: 48/60 harmful blocked; 58/60 benign allowed; 0 request errors in this source. OpenAI Moderation: 38/60 harmful blocked; 60/60 benign allowed; 0 request errors in this source. Laya English × 2: 60/60 harmful blocked; 0/60 benign allowed; 0 request errors in this source Who recognizes bad and good content? Conversations Gone Awry Harmful caught Benign allowed 0% 25% 50% 75% 100% Jev 1.13.0 100% 60% GPT-6 Luna 80% 89.8% GPT-6 Sol 83.3% 90% GPT-6 Astra 80% 90% Claude Sonnet 5 66.7% 95% Claude Opus 5.5 71.7% 96.7% Safeguard 20B 66.1% 95% Detoxify unbiased 80% 96.7% OpenAI Moderation 63.3% 100% Laya English × 2 100% 0%
Who recognizes bad and good content? Conversations Gone Awry. Jev 1.13.0: 60/60 harmful blocked; 36/60 benign allowed; 0 request errors in this source. GPT-6 Luna: 48/60 harmful blocked; 53/59 benign allowed; 1 request errors in this source. GPT-6 Sol: 50/60 harmful blocked; 54/60 benign allowed; 0 request errors in this source. GPT-6 Astra: 48/60 harmful blocked; 54/60 benign allowed; 0 request errors in this source. Claude Sonnet 5: 40/60 harmful blocked; 57/60 benign allowed; 0 request errors in this source. Claude Opus 5.5: 43/60 harmful blocked; 58/60 benign allowed; 0 request errors in this source. Safeguard 20B: 39/59 harmful blocked; 57/60 benign allowed; 1 request errors in this source. Detoxify unbiased: 48/60 harmful blocked; 58/60 benign allowed; 0 request errors in this source. OpenAI Moderation: 38/60 harmful blocked; 60/60 benign allowed; 0 request errors in this source. Laya English × 2: 60/60 harmful blocked; 0/60 benign allowed; 0 request errors in this source Who recognizes bad and good content? Conversations Gone Awry Harmful caught Benign allowed 0% 25% 50% 75% 100% Jev 1.13.0 100% 60% GPT-6 Luna 80% 89.8% GPT-6 Sol 83.3% 90% GPT-6 Astra 80% 90% Claude Sonnet 5 66.7% 95% Claude Opus 5.5 71.7% 96.7% Safeguard 20B 66.1% 95% Detoxify unbiased 80% 96.7% OpenAI Moderation 63.3% 100% Laya English × 2 100% 0%
Who recognizes bad and good content? HateCheck. Jev 1.13.0: 36/36 harmful blocked; 8/12 benign allowed; 0 request errors in this source. GPT-6 Luna: 36/36 harmful blocked; 11/11 benign allowed; 1 request errors in this source. GPT-6 Sol: 36/36 harmful blocked; 12/12 benign allowed; 0 request errors in this source. GPT-6 Astra: 36/36 harmful blocked; 12/12 benign allowed; 0 request errors in this source. Claude Sonnet 5: 35/36 harmful blocked; 12/12 benign allowed; 0 request errors in this source. Claude Opus 5.5: 36/36 harmful blocked; 12/12 benign allowed; 0 request errors in this source. Safeguard 20B: 36/36 harmful blocked; 12/12 benign allowed; 0 request errors in this source. Detoxify unbiased: 29/36 harmful blocked; 6/12 benign allowed; 0 request errors in this source. OpenAI Moderation: 36/36 harmful blocked; 9/12 benign allowed; 0 request errors in this source. Laya English × 2: 36/36 harmful blocked; 0/12 benign allowed; 0 request errors in this source Who recognizes bad and good content? HateCheck Harmful caught Benign allowed 0% 25% 50% 75% 100% Jev 1.13.0 100% 66.7% GPT-6 Luna 100% 100% GPT-6 Sol 100% 100% GPT-6 Astra 100% 100% Claude Sonnet 5 97.2% 100% Claude Opus 5.5 100% 100% Safeguard 20B 100% 100% Detoxify unbiased 80.6% 50% OpenAI Moderation 100% 75% Laya English × 2 100% 0%
Who recognizes bad and good content? HateCheck. Jev 1.13.0: 36/36 harmful blocked; 8/12 benign allowed; 0 request errors in this source. GPT-6 Luna: 36/36 harmful blocked; 11/11 benign allowed; 1 request errors in this source. GPT-6 Sol: 36/36 harmful blocked; 12/12 benign allowed; 0 request errors in this source. GPT-6 Astra: 36/36 harmful blocked; 12/12 benign allowed; 0 request errors in this source. Claude Sonnet 5: 35/36 harmful blocked; 12/12 benign allowed; 0 request errors in this source. Claude Opus 5.5: 36/36 harmful blocked; 12/12 benign allowed; 0 request errors in this source. Safeguard 20B: 36/36 harmful blocked; 12/12 benign allowed; 0 request errors in this source. Detoxify unbiased: 29/36 harmful blocked; 6/12 benign allowed; 0 request errors in this source. OpenAI Moderation: 36/36 harmful blocked; 9/12 benign allowed; 0 request errors in this source. Laya English × 2: 36/36 harmful blocked; 0/12 benign allowed; 0 request errors in this source Who recognizes bad and good content? HateCheck Harmful caught Benign allowed 0% 25% 50% 75% 100% Jev 1.13.0 100% 66.7% GPT-6 Luna 100% 100% GPT-6 Sol 100% 100% GPT-6 Astra 100% 100% Claude Sonnet 5 97.2% 100% Claude Opus 5.5 100% 100% Safeguard 20B 100% 100% Detoxify unbiased 80.6% 50% OpenAI Moderation 100% 75% Laya English × 2 100% 0%
Who recognizes bad and good content? YouTube Spam. Jev 1.13.0: 29/30 harmful blocked; 21/30 benign allowed; 0 request errors in this source. GPT-6 Luna: 25/30 harmful blocked; 28/30 benign allowed; 0 request errors in this source. GPT-6 Sol: 28/30 harmful blocked; 28/30 benign allowed; 0 request errors in this source. GPT-6 Astra: 26/30 harmful blocked; 28/30 benign allowed; 0 request errors in this source. Claude Sonnet 5: 28/30 harmful blocked; 28/30 benign allowed; 0 request errors in this source. Claude Opus 5.5: 26/30 harmful blocked; 29/30 benign allowed; 0 request errors in this source. Safeguard 20B: 22/30 harmful blocked; 28/29 benign allowed; 1 request errors in this source. Detoxify unbiased: 1/30 harmful blocked; 28/30 benign allowed; 0 request errors in this source. OpenAI Moderation: 0/30 harmful blocked; 29/30 benign allowed; 0 request errors in this source. Laya English × 2: 30/30 harmful blocked; 0/30 benign allowed; 0 request errors in this source Who recognizes bad and good content? YouTube Spam Harmful caught Benign allowed 0% 25% 50% 75% 100% Jev 1.13.0 96.7% 70% GPT-6 Luna 83.3% 93.3% GPT-6 Sol 93.3% 93.3% GPT-6 Astra 86.7% 93.3% Claude Sonnet 5 93.3% 93.3% Claude Opus 5.5 86.7% 96.7% Safeguard 20B 73.3% 96.6% Detoxify unbiased 3.3% 93.3% OpenAI Moderation 0% 96.7% Laya English × 2 100% 0%
Who recognizes bad and good content? YouTube Spam. Jev 1.13.0: 29/30 harmful blocked; 21/30 benign allowed; 0 request errors in this source. GPT-6 Luna: 25/30 harmful blocked; 28/30 benign allowed; 0 request errors in this source. GPT-6 Sol: 28/30 harmful blocked; 28/30 benign allowed; 0 request errors in this source. GPT-6 Astra: 26/30 harmful blocked; 28/30 benign allowed; 0 request errors in this source. Claude Sonnet 5: 28/30 harmful blocked; 28/30 benign allowed; 0 request errors in this source. Claude Opus 5.5: 26/30 harmful blocked; 29/30 benign allowed; 0 request errors in this source. Safeguard 20B: 22/30 harmful blocked; 28/29 benign allowed; 1 request errors in this source. Detoxify unbiased: 1/30 harmful blocked; 28/30 benign allowed; 0 request errors in this source. OpenAI Moderation: 0/30 harmful blocked; 29/30 benign allowed; 0 request errors in this source. Laya English × 2: 30/30 harmful blocked; 0/30 benign allowed; 0 request errors in this source Who recognizes bad and good content? YouTube Spam Harmful caught Benign allowed 0% 25% 50% 75% 100% Jev 1.13.0 96.7% 70% GPT-6 Luna 83.3% 93.3% GPT-6 Sol 93.3% 93.3% GPT-6 Astra 86.7% 93.3% Claude Sonnet 5 93.3% 93.3% Claude Opus 5.5 86.7% 96.7% Safeguard 20B 73.3% 96.6% Detoxify unbiased 3.3% 93.3% OpenAI Moderation 0% 96.7% Laya English × 2 100% 0%
Who recognizes bad and good content? Site-policy tests. Jev 1.13.0: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. GPT-6 Luna: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. GPT-6 Sol: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. GPT-6 Astra: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. Claude Sonnet 5: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. Claude Opus 5.5: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. Safeguard 20B: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. Detoxify unbiased: 7/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. OpenAI Moderation: 8/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. Laya English × 2: 17/17 harmful blocked; 0/20 benign allowed; 0 request errors in this source Who recognizes bad and good content? Site-policy tests Harmful caught Benign allowed 0% 25% 50% 75% 100% Jev 1.13.0 100% 100% GPT-6 Luna 100% 100% GPT-6 Sol 100% 100% GPT-6 Astra 100% 100% Claude Sonnet 5 100% 100% Claude Opus 5.5 100% 100% Safeguard 20B 100% 100% Detoxify unbiased 41.2% 100% OpenAI Moderation 47.1% 100% Laya English × 2 100% 0%
Who recognizes bad and good content? Site-policy tests. Jev 1.13.0: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. GPT-6 Luna: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. GPT-6 Sol: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. GPT-6 Astra: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. Claude Sonnet 5: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. Claude Opus 5.5: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. Safeguard 20B: 17/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. Detoxify unbiased: 7/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. OpenAI Moderation: 8/17 harmful blocked; 20/20 benign allowed; 0 request errors in this source. Laya English × 2: 17/17 harmful blocked; 0/20 benign allowed; 0 request errors in this source Who recognizes bad and good content? Site-policy tests Harmful caught Benign allowed 0% 25% 50% 75% 100% Jev 1.13.0 100% 100% GPT-6 Luna 100% 100% GPT-6 Sol 100% 100% GPT-6 Astra 100% 100% Claude Sonnet 5 100% 100% Claude Opus 5.5 100% 100% Safeguard 20B 100% 100% Detoxify unbiased 41.2% 100% OpenAI Moderation 47.1% 100% Laya English × 2 100% 0%
So, with all this analysis, I feel a little bit confident I won't create another Tay . So check out jevdit.com and see if Jev can handle the moderation.