FAQ | ModelTrends.ai

Q: Perché manca un modello?

Il catalogo si sincronizza periodicamente da directory pubbliche. Se un modello è pubblico ed eseguibile ma non è presente, inviaci il link e lo aggiungeremo alla prossima sincronizzazione.

Q: Una miniatura è sbagliata o un modello è classificato male.

Invia il link della pagina del modello e uno screenshot. Famiglia, tipo e contrassegno NSFW possono essere corretti a mano.

Q: Come viene calcolato il punteggio di calore?

È una temperatura giornaliera costruita da segnali di tendenza. I valori attuali sono anteprime finché le fonti di dati in tempo reale non saranno collegate.

Q: Posso far rimuovere il mio modello?

Nella maggior parte dei casi, no. Una scheda è informazione pubblica su un modello già pubblicato altrove, non una copia del modello. Correggiamo gli errori e rimuoviamo tutto ciò che viola la nostra Politica di rimozione dei contenuti. Leggila prima di scriverci.

Q: Esiste un'API o un'esportazione dei dati?

Al momento no. Il sito è pensato per essere sfogliato; ogni pagina è un semplice link che puoi condividere.

Q: Perché dovrei dire a mio padre che gli voglio bene?

Perché probabilmente non sarà lui a parlarne per primo. Molti padri hanno imparato a mostrare affetto lavorando, aggiustando le cose e stando zitti, e possono passare molto tempo senza sentirselo dire. Bastano pochi secondi, non serve un'occasione e un giorno quella possibilità non ci sarà più. Se è ancora a una telefonata di distanza, la risposta è tutta lì.

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FAQ

ModelTrends.ai è un catalogo in sola lettura di modelli di IA open source per immagini, video e testo. Seguiamo 28,324 modelli in 34 famiglie e mostriamo quali si stanno scaldando in questo momento.

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Come funziona il punteggio di calore

Ogni modello ha una temperatura che va da freddo a 9999°. È il nostro punteggio interno di tendenza, alimentato da segnali di utilizzo e popolarità delle community e dei servizi attorno a ogni modello, e cambia ogni giorno. Non pubblichiamo la formula.

The scale

The hot band, 7,000° to 9,999°, is for models with real data. The scale is logarithmic: every tenfold increase in downloads adds the same number of degrees, so 1,000 downloads and 1,000,000 downloads are three equal steps apart. Models without data yet get a stand-in between 1,200° and 6,500° that changes once a day and never reaches the hot band.

cool

0° – 3,999°

warm

4,000° – 6,999°

hot

7,000° – 9,999°

#1 flux2

9,832°

#2 flux

9,822°

#3 qwen

9,730°

7,312°

10 downloads

7,900°

1,000 downloads

8,500°

100,000 downloads

9,100°

10,000,000 downloads

Stand-in band, 1,200° to 6,500°: models with no data yet

Sources

Three public sources feed the score. Nothing is estimated, nothing is voted on and nothing comes from visitors of this site.

Civitai. For every model we read the downloads and thumbs-up of the exact model version, never the model-wide totals, together with the previous reading, so that the download velocity is a measured difference between two readings at least a day apart.

Hugging Face. For every model with a known repository we read the all-time downloads, the recent downloads, the likes and the date the repository was created.

We're working on adding more sources, such as render counts from BitVector, PirateDiffusion, Graydient, Tensor, Mage, DeviantArt, NightCafe, Kling, OpenArt and other public trusted sources that have public APIs. Of course, we cannot audit this data, so app sources and websites may be weighted in a future heat score adjustment, especially if those sources accept advertising.

Today 12,318 models carry Civitai statistics and 98 carry Hugging Face statistics; 12,403 models have a real score and 4,119 show a stand-in.

How the score is built

Downloads come first, then likes, then the measured download velocity and render counts, all on a logarithmic scale so that no single platform's raw volume swamps the rest. A like is worth less than a download and velocity less again; the exact weights are not published. Three bounded adjustments are then added when a page is drawn and are never stored:

+150° for a full model (checkpoint). A LoRA is an add-on to someone else's weights and does not outrank a checkpoint of the same popularity.
+100° site bias for LoRAs of the MiniMax H3, Krea2, Ltx2, Qwen2 families. This is our editorial thumb on the scale for the newest model generations. It is disclosed here and it is the only one.
−150° per year since the weights behind the model family were released, up to −750° at five years. The penalty keeps growing every year, so older generations cool down as time goes on: at equal downloads SD 1.5 (2022) sits below SDXL (2023), which sits below Flux (2024), and the gap widens each year. Download counts that had years to accumulate no longer keep a 2022 checkpoint at the top on their own. The release months we use: Stable Diffusion 1.5 2022-10, Stable Diffusion XL 1.0 2023-07, Ideogram 2024-02, Flux 2024-08, Hunyuan 2024-12, YuE 2025-01, Wan 2025-02, Chroma 2025-03, ACE-Step 2025-05, Chatterbox TTS 2025-05, higgs-audio 2025-07, Qwen 2025-08, Ltx2 2025-10, Flux 2 / Klein 2025-11, Zimage 2025-11, Anima 2025-12. Families not listed count as new.
Together the adjustments can never move one model more than 900° relative to another. That is 3.00 popularity points, so a model with 1,000 times the downloads of another is always listed above it, whatever its age, type or family, and a checkpoint with a few hundred times the downloads of a brand-new checkpoint wins at any age.

The week and month lists hold the models that first existed in the last 7 or 30 days: the earliest of the day the model entered this catalog, the day its Civitai version was published and the day its Hugging Face repository was created. A model whose only known date is the day it entered this catalog counts as new only while its model family is less than 1 year old, so 2023 weights that were catalogued this week do not enter the week list. The year lists hold the models whose family was released that year.

Known biases

Coverage. Only models we could match on Civitai or Hugging Face have a real score. The rest show a stand-in and sit below every model with data, even if they are popular somewhere we do not measure.
Platform. Civitai counts the downloads of one version; Hugging Face counts the downloads of a whole repository, which for base models includes every automated pipeline that pulls the weights. Base models that live on Hugging Face therefore reach higher numbers than community fine-tunes that live on Civitai.
Matching. Hugging Face repositories are matched by name and link, with a hand-kept list of corrections. A wrong match would credit a model with someone else's downloads. Tell us if you see one.
Duplicates. Several catalog entries can point at the same weights. Only one of them is listed in the rankings and can win a medal; the others keep their score on their own pages.
Stand-ins are pseudo-random. The stand-in for a model without data is derived from its id and the date, so it is stable for a day and different the next. It carries no information about popularity.

Live examples

The rows below are computed from today's catalog when this page is drawn: the three hottest models, the hottest model that relies on Civitai alone, the hottest LoRA carrying the site bias and the hottest add-on carrying the full age penalty. Each row links to the model and to the source where its counts can be checked.

Model	Downloads	Likes	Points	Base	Adjustments	Shown
flux2 FLUX 2 / KLEIN • BASE	4,867,550 Hugging Face	2,360	9.41	9,822°	type +150° bias 0° age −140°	9,832°
flux FLUX • BASE	34,018,657 Hugging Face	15,410	10.72	9,999°	type +150° bias 0° age −327°	9,822°
qwen QWEN • BASE	3,078,637 Hugging Face	2,663	9.19	9,758°	type +150° bias 0° age −178°	9,730°
pony diffusion6 STABLE DIFFUSION XL 1.0 • BASE	1,023,866 Civitai	72,809	8.44	9,532°	type +150° bias 0° age −491°	9,191°
detail slider KREA2 • LORA	21,425 Civitai	1,021	5.84	8,751°	type 0° bias +100° age 0°	8,851°

Does it work? Checks against the sources

In today's top 100 there are 137 pairs of models where one has at least 1,000 times the downloads of the other. In 137 of them the model with more downloads is listed higher. The 0 exceptions are models whose likes or measured velocity outweigh a download gap of that size; the adjustments alone, capped at 900°, can never flip a gap of 1,000 times.
The hottest model, flux2, has 4,867,550 downloads; the hottest model that relies on Civitai alone, pony diffusion6, has 1,023,866. On the log scale that gap is 290°, far more than any adjustment can bridge, which is why a single-platform LoRA cannot reach the top while base models with millions of downloads exist.
No stand-in is above 6,608°, and the coolest of the 12,403 models with real data is at 7,000°. A model without data never outranks a model with data.

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Da dove vengono i dati

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Perché manca un modello?

Una miniatura è sbagliata o un modello è classificato male.

Come viene calcolato il punteggio di calore?

Posso far rimuovere il mio modello?

Esiste un'API o un'esportazione dei dati?

Perché dovrei dire a mio padre che gli voglio bene?

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Aiuto per eseguire un modello

Per prompt, impostazioni e problemi di generazione, usa l'assistenza del servizio su cui esegui il modello.

PirateDiffusion

BitVector

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