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Community quantizations of the pruned FL2VA denoiser (the diffusion transformer, about 20 B parameters) of MiniMax-H3, the model that generates video with a synchronized stereo audio track. Made with stable-diffusion.cpp. Independent work, not made or endorsed by MiniMax or Comfy-Org. This repository holds the **denoiser** and unmodified copies of the two **VAEs**. The Qwen3-VL text encoder is a separate file: an abliterated ("uncensored") build is available as a separate repository, Sakura-MiniMax-H3-Uncensored-GGUF; unchanged encoders in GGUF exist from other community members (for example leejet/MiniMax-H3-GGUF). ComfyUI: not tested by us; the community GGUF loader fork named in leejet's repository is the one to try.

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> For adults only; you are responsible for what you generate and for the laws that apply to you. The language weights come from a model whose refusals were removed and whose text generation breaks down on harmful prompts (see below); what this changes in the video we measured only for six non-explicit prompts (see below). Do not use it to depict minors in any sexual or abusive context, or to create sexual or defamatory images of real persons without their consent. Do not put it into a public service without your own moderation. The **text encoder** of MiniMax-H3 (the first 50 language layers of Qwen3-VL-32B plus its vision tower, passed to the video model with `--llm`) with the language weights of an **abliterated (uncensored)** Qwen3-VL-32B-Instruct, as GGUF for stable-diffusion.cpp. Independent work, not made, reviewed or endorsed by MiniMax, Comfy-Org, Qwen / Alibaba or llmfan46. - The text encoder shipped inside MiniMax-H3 is **the unmodified Qwen3-VL-32B-Instruct**: the sha256 of all 14 `text_encoder` shards of `MiniMaxAI/MiniMax-H3` equal those of `Qwen/Qwen3-VL-32B-Instruct`. MiniMax-H3 uses it truncated to 50 language layers and without the final language-model norm. - We built the encoder from an **abliterated checkpoint of that model made by a community member** (llmfan46's abliterated Qwen3-VL-32B-Instruct, Apache-2.0, revision `c44b949b30d111666a5ed9851c5cd633ed39b070`; sha256 of both shards checked against the Hub). **We did not run the ablation ourselves** for this repository. - Tensors were copied one by one into the layout of the Comfy-Org H3 encoder file (902 tensors; names, dtypes and shapes equal that file; the 14 layers 50 to 63, the final norm and the output head are dropped), then converted with `sd-cli -M convert`.

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**Built with Qwen.** Community quantization of Qwen/Qwen-Image-2.1-Turbo (8-step distilled, 7B DiT) with an **abliterated text encoder**. Independent work, not made or endorsed by Alibaba/Qwen. **Non-commercial use only** (Qwen RESEARCH LICENSE AGREEMENT, copy in `LICENSE`). For adults only; you are responsible for what you generate and for the laws that apply to you. Q8_0 image model and our 8bit uncensored text encoder, stable-diffusion.cpp (Vulkan, Radeon 8060S), 1024x1024, 8 steps, CFG 1.0, `euler`, official Turbo sigmas. One seed per prompt and no re-rolls; the prompts themselves were chosen from a larger set of candidates. About 77 s per image including model loading; the GPU memory in use on our machine peaked at 18.3 GiB while generating (Windows counter for the whole GPU, 1.5 GiB of it were in use before the run). The images were made with stable-diffusion.cpp, not with ComfyUI. The prompts are neutral. These images say nothing about what the ablated text encoder changes for restricted content; they only show that ordinary prompts still work. The same nine prompts and seeds are used in the sibling repository Sakura-Qwen-Image-2.1-Turbo-GGUF with the official encoder, so the two sets can be compared.

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月間トークン数を調整してAPI費用を比較。

1 M = 100万トークン・米ドル
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収集済みの比較可能な100万トークン当たり米ドル料金です。キャッシュ割引、段階料金、追加推論出力、税金は含みません。最新料金は出典で確認してください。

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API料金はどう比較しますか？+

入力・出力・キャッシュ料金を分け、同じ用途と使用量で総費用を比較します。画像・音声・動画は枚数、時間、解像度で課金される場合があります。

オープンウェイトは無料で商用利用できますか？+

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