Finding and training male character LoRAs

If you search Civitai for male character LoRAs, the shortage is obvious within seconds. The platform's own tag index counts roughly 29,300 models tagged "male" against about 32,300 tagged "female" — a real but modest gap. Within the character-specific subset, however, the imbalance feels much larger, which is why several community-built masterlists exist entirely to catalogue the male side. This guide covers what the numbers actually show, what training metadata reveals about captioning choices, and which directories are still worth your time in 2026. See how LoRA training works generally for broader context.

TL;DR

• Civitai's tag index shows a 29,306-to-32,291 male-vs-female model split — real but modest. The perceived skew is concentrated in character LoRAs specifically.
• At least one verified male character LoRA uses booru-style trigger words with escaped parentheses; one trainer recommends staying at or below weight 0.6.
• Several community masterlists exist, but most were paused in 2024. Use them as starting points, not exhaustive indexes.

The gender gap on Civitai, by the numbers

Civitai's public tag pages list 29,306 models tagged "male" and 32,291 tagged "female" as of 2026-07-28. That is a roughly 52:48 split across all model types — checkpoints, embeddings, style LoRAs, and character LoRAs combined. The gap is real, but it is not the overwhelming skew that casual browsing suggests.

Several curators explicitly cite the perception that female characters dominate search results. One long-running male-model masterlist opens with the observation that the sheer volume of female character models makes it easy for male-focused resources to get lost. That perception is specific to character LoRAs, not the entire tag pool.

What changes when you train a male character LoRA

No published source systematically compares male versus female LoRA captioning practices, so any explanation of the difference would be inference, not documentation. What follows is drawn from verified model pages and curator notes only.

From the model pages that expose training metadata, at least one verified male character LoRA — the Guts model — uses trigger words formatted with booru-style escaping, such as guts \(berserk\) and guts \(armor\). One curator's general note reinforces a split between captioning paradigms: some LoRAs work best with anime-style booru tags, while others respond better to typical captions.

The Suyo double-pack (two male characters from a webcomic) explicitly recommends keeping LoRA weight at or below 0.6 and supplementing the prompt with explicit physical descriptors. Whether other male character LoRAs need the same treatment is undocumented.

If you are comparing how LoRA training works across genders, treat the metadata as a hint, not a rulebook. Step counts, epoch counts, and trigger-word formats vary by trainer and by source material.

Community directories worth using

Because Civitai's native search does not group models by franchise or gender reliably, users maintain separate articles that function as character-level indexes. The directories relevant to male character LoRAs break down by scope:

• Main masterlist: base models, synthetic men, and resources
• Anime, manga, yaoi, bara, and manhwa characters
• Fictional characters and video games
• Real people

Directory comparison

Note: Mature-content versions of these articles moved to civitai.red after Civitai split adult material onto a separate domain. The main site now redirects with the message: "Mature content now lives on civitai.red."

When you are choosing a base model for character LoRAs, start from the directory that matches your property type, then verify each link individually. Several lists were paused in 2024, so coverage gaps and broken URLs are common.

Common errors and fixes

FAQ

Q: Why are there so few male character LoRAs compared to female ones? A: Civitai's tag index shows a roughly 10% gap at the platform level, but character-specific male LoRAs appear thinner than that simple ratio suggests. Multiple curators maintain masterlists specifically because male character models are harder to discover through ordinary search.

Q: How do I find male character LoRAs for anime and video game characters? A: Start with the genre-specific directories: anime and manga, fictional characters and video games, or real people, depending on the property. Within each, scan by franchise. Note that several lists were paused in 2024, so cross-check individual model pages for broken links.

Q: What is the best captioning style for male character LoRAs? A: Evidence is limited. One verified male character LoRA (Guts) uses booru-style tags with escaped parentheses; other trainers report success with natural-language prompts. One curator notes that results depend heavily on which paradigm a given LoRA was trained with. There is no single best approach — match the prompt style to the model.

Q: Are male character LoRAs harder to train than female ones? A: Verified model pages do not provide a side-by-side difficulty comparison. What is documented is that some male character LoRAs need explicit physical-descriptor prompts and conservative weight settings to avoid unintended body defaults.

Q: What weight should I use for male character LoRAs? A: One verified male character double-pack recommends staying at or below 0.6, with explicit prompt supplementation. Other models may need different values; test incrementally.

Q: Will these directories stay updated? A: No. The anime/manga list was paused on January 1, 2024, and the main masterlist was paused in July 2024. The fictional-characters and real-people lists were updated less frequently by late 2023. Expect gaps and broken links; verify each model page individually.

Q: Where do I look if a male character LoRA is missing from Civitai? A: Search by character name directly on Civitai and check adjacent platforms. The directories are curated by volunteers and do not claim completeness; one Arknights guide explicitly states it is the maintainer's personal index rather than an exhaustive catalogue.

Sources