CivArchive
    Gurren Lagann Anime Style Lora H3 - v1.0
    NSFW

    Trained on the same dataset as my Krea 2 gurren lagann lora. Images only, 441 screen captures from the show (pre-time skip only). I think I will try video training later, right now video training for H3 is not super great, images is perfectly fine and fast. Characters sort of work, I think this is more useful for style instead of character creation, a separately trained character lora probably would be better. Trained on FLV2A model.

    The 17k checkpoint is best, but give the 9.9k steps a try if you think its overcooked. Not tested with lightx speed up loras. Recommended euler beta57 20 steps at 1 strength.

    Style trigger:

    "2d anime style, Gurren Lagann Style"

    Character trigger:

    "char_firstname"

    Here is how to recreate some characters (check the captions data for more). Some are doable but a bunch not so much.

    Yoko:

    char_yoko, A woman with long red spiky hair tied in a long pony tail and chopsticks and skull accessory, red flame-patterned black bikini top, light pink scarf, black shorts with a white studded belt, pink thigh-high stockings, fingerless black gloves, and white and red boots. She holds a massive dark grey, hexagonal-barreled rifle.

    Simon:

    char_simon, A young man (or “boy”) with spiky dark blue hair, a blue jacket over his bare torso, and red goggles on his head 

    Kamina:

    char_kamina, A muscular man with spiky blue hair and blue spiral tattoos. He is wearing orange frameless pointed triangle sunglasses and a red tattered cape. He has bandages on his forearms

    Nia:

    char_nia, A young woman with wavy blonde and light blue hair and teal eyes with red pupils cross-like in a  floral shape. She wears a pink and white dress with a large gold belt and cuffs. And an elaborate golden collar with red and green gems, a red tie, and a pink and white hair accessory.

    Gurren & Lagann:

    A humanoid mecha (might want to describe about the face on his torso etc, but its not captioned much). Be sure to mention the samurai horns on the head if you want that etc. Every form of them is in the data too (flying mode, battle ship etc.)

    Viral:

    char_viral, A man with shaggy blonde hair that covers one eye. He wears a jacket with a white fur-lined collar and red shoulder pads.

    Mecha:

    All mecha in this are labeled using “mecha” you can say like “whale-like mecha” or “turle-like mecha” etc. to get different types. There is probably all the different ones in the training data. Just use this phrase “mecha” to trigger it.

    Beastmen = “creature” , ie turtle-like creature, etc.

    Buta:

    char_buta, A small, brown, pill-shaped pink pig-mole creature with two long, thin antennae, a curly tail, whiskers and round sunglasses

    Lordgenome:

    char_lordgenome, A large, extremely muscular man with a shaved head, a dark stylized beard, and intense, light-colored eyes. He is shirtless wearing a dark garment with two large, silver, U-shaped bracelets on his arms. (I guess I missed captioning the beard, try adding that word in too)

    There is more, I should have covered every character major or minor in the first season. So try yourself to describe them or check the captions. the syntax is char_(firstname) + a description of their outfit and appearance.

    Training

    Trained using Musubi Fork by Akanetendo25 with --h3_spatial_density_jitter 0.2 --h3_guidance_distillation_scale 3.5 --h3_base_preservation_loss_weight 0.02 \ and using adam8bit 5e-5. At rank 16, 1376 x 768 repeats 1. On a 5090 locally it used only around 25gb or so of vram and trained around 1.5s/it, very fast. It picks up the style pretty quick, I think around 5k steps even noticeable differences, I think 9.9k was quite usable but I like where 17k steps ended up.

    Description

    FAQ

    Comments (12)

    tomookazaki87856Aug 27, 2026· 1 reaction
    CivitAI

    Can i use it too for my Anime Charakter to use better Animation style by ref2v ?

    The_Last_Goblin_KingAug 27, 2026
    CivitAI

    Joker sitting in a cell <clap, clap, clap>

    JellaiAug 27, 2026· 2 reactions
    CivitAI

    Holy shit. I've been following your loras since the beginning, and Minimax seems to be taking on this style better than any video model you've tried yet. How rough was the training process in terms of time/compute?

    H3's existing animation training really shines here. The fact that you could do this with just images is super exciting.

    tazmannner379
    Author
    Aug 27, 2026· 1 reaction

    Yes its truly exciting to finally have a model that was trained properly on 2d anime. This was super painless. It took me like 30 mins to get the dataset ready to train probably. 1.5s/it on a 5090 and less than a day to train up to 17k steps.

    JellaiAug 27, 2026

    @tazmannner379 Holy moly! I suspect that if I were to try to train something like X-Men 97, I might actually have to use some animation video data, but I'm feeling pretty confident seeing this that I could train practically any anime only on images. Stuff like Redline or Ping Pong might be tricky?

    JellaiAug 27, 2026

    This is the first time I've felt that Minimax utterly mops the floor with Wan 2.2 for purely visual results. Not even in the same ballpark. It's so exciting. Also, it's nuts how small the lora can be for this level of quality. The pre-existing animation training is SO useful.

    wktraAug 28, 2026
    CivitAI

    OMG THIS IS GORGEOUS!

    I've wasted so much money trying to train minimax H3 on my art style. I used 250 images and captioned everything in natural language but the similarity results are horrible. I've gotten NO help from other forums, even on the AI Toolkit discord.

    What program did you use to train and what settings did you use? Resolution of the dataset? I am giving you buzz because I'm desperate! 😭

    --Edit: OMG I'M SO STUPID. I just saw your settings in the description.

    Could you share info about the dataset? resolution? natural language example from a typical caption?

    tazmannner379
    Author
    Aug 28, 2026

    The dataset is screen captures from the show at 1920x1080 resolution but its trained on 1376x768 resolution. I caption everything in the syntax of H3 and use the trigger words mentioned in the description. Here is an example:

    integrated_multimodal_description: [Shot 1] 2d anime style, Gurren Lagann Style, high-angle medium shot. Three people are crammed together in a narrow space with light brown walls. In the foreground, a young woman char_Yoko with long, dark purple hair, a white skull accessory, a dark bikini top, and a studded white belt is aiming a large, dark green, tripod-mounted rifle through its scope. Directly behind her, a shirtless man char_Kamina with light blue hair and blue tattoos looks on with a surprised expression. Behind him, a third person char_Simon with dark hair and a red headband is visible. The camera remains in a Static Shot as the characters maintain their positions. overall_soundscape: N/A non_diegetic_music: N/A

    Musubi tuner fork is a little more complicated to use, but I think better than ai toolkit.

    wktraAug 28, 2026

    @tazmannner379 OH WOW! thank you!

    did you hand caption it yourself? or use something like taggui to help? or did you use a chatbot like chatgpt or gemini for each image?

    tazmannner379
    Author
    Aug 28, 2026

    @wktra Gemini for captioning, its really good. Then I used Gemma 4 12b locally to convert them to h3 syntax since this dataset existed before h3. I had to go through and a quick touch up here and there but for the most part it was fine

    wktraAug 28, 2026

    @tazmannner379 thank you so much!!!

    tazmannner379
    Author
    Aug 28, 2026

    @wktra no problem you may get a better result giving this file to gemini before captioning: https://github.com/MiniMax-AI/MiniMax-H3/blob/main/skills/h3-prompt-writing/references/base-en.txt

    LORA
    MiniMax H3

    Details

    Downloads
    312
    Platform
    CivitAI
    Platform Status
    Available
    Created
    8/27/2026
    Updated
    8/28/2026
    Deleted
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    GL_H3_V1-step00017250.safetensors

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