An adult photographic-content LoRA for MOSS-Image-SFT or MOSS-Image-Base, with **MOSS-Image-SFT preferred for inference**. It is tuned for explicit adult portraiture, nude poses, indoor scenes, and close photographic compositions. The repository-root adapter is now the focused 1,750-step checkpoint trained on 130 images; start at scale `0.8`. The former 2,000-step, 221-image adapter is preserved under `original-checkpoint-2000/` and remains available at its recommended scale of `0.7`. A GGUF conversion (44% less VRAM on Q8 and 66% less VRAM on Q4) is also available here: https://huggingface.co/axiomofmind/Moss-image-nsfw-uncensored-lora-GGUF which can be used with MOSS-Image-SFT-GGUF

译文排队中 · 当前显示来源原文

图像生成

输入文本→ 输出图像

价格待核验多模态与渠道费用须分别核对

查看详情 ↗

加入对比来源 / 文档 ↗

Moss-image-nsfw-uncensored-lora-GGUF

axiomofmind

Separate F16 GGUF conversions of the adult-photography LoRAs from axiomofmind/Moss-image-nsfw-uncensored-lora. They are designed to be applied at inference time to axiomofmind/Moss-Image-SFT-GGUF, keeping the adapter strength adjustable without creating a merged model for every base quantization or scale. This repository contains the **LoRA adapter only**. It does not contain the base diffusion transformer, Qwen3.5 text encoder, tokenizer, or VAE. > **Adult-content notice:** The source adapter is intended for lawful creative generation involving clearly adult fictional subjects and can produce explicit sexual imagery. It is for adults only in jurisdictions where such content is lawful. Do not use it for minors or age-ambiguous subjects, abuse, exploitation, coercion, non-consensual imagery, or sexualized depictions of identifiable real people without explicit consent.

译文排队中 · 当前显示来源原文

图像生成

输入文本→ 输出图像

价格待核验多模态与渠道费用须分别核对

查看详情 ↗

加入对比来源 / 文档 ↗

Moss-image-psychedelic-lora

axiomofmind

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

基础资料已收录 · 缺失资料后续补充

图像生成

输入文本→ 输出图像

价格待核验多模态与渠道费用须分别核对

查看详情 ↗

加入对比来源 / 文档 ↗

Moss-Image-SFT-GGUF

axiomofmind

Unofficial GGUF conversions of OpenMOSS-Team/MOSS-Image-SFT, a 5B text-to-image diffusion transformer fine-tuned from MOSS-Image-Base. These files contain the **diffusion transformer (DiT) only**. They still require a Qwen3.5-9B text encoder, the official MOSS tokenizer, and the MOSS / FLUX.2 VAE. They are image-model GGUFs for compatible diffusion runtimes—not text LLMs for Ollama, LM Studio, or llama.cpp text generation. Both are GGUF v3 files with 463 tensors and `general.architecture=moss_image` metadata. Checksums are also provided in `SHA256SUMS`.

译文排队中 · 当前显示来源原文

图像生成

输入文本→ 输出图像

价格待核验多模态与渠道费用须分别核对

查看详情 ↗

加入对比来源 / 文档 ↗

COST EXPLORER

好模型，也要算好成本。

费用分析

调整月度 Token 用量，直观比较不同模型的预估 API 开支。

每月输入 Token 10 M每月输出 Token 2 M1 M = 100 万 Token · 美元计价
仅比较同一渠道的基础文本 Token 报价

使用已采集且单位可比的 USD / 百万 Token 渠道报价。报价为采集时快照；不计缓存优惠、阶梯价、推理额外输出与税费，请以来源的当前报价为准。

MODEL HANDBOOK

读懂模型，再做选择

选型与常见问题

API 价格应该怎么比较？+

先区分输入、输出和缓存价格，再使用同一任务和用量估算总费用。图像、音频和视频可能按张、时长或分辨率计费，不能直接与 Token 单价比较。

开放权重，就代表可以免费商用吗？+

不一定。必须逐一核对具体模型版本的许可证、商用限制及使用政策。自己部署还需要考虑显存、推理资源和运维费用。

排行榜第一，就是最适合我的模型吗？+

榜单取决于测试任务、版本与评测方法。建议用实际业务样本比较准确性、时延、稳定性和成本，再选择模型。

找到适合你的 AI 模型。

探索 AI 模型 12

Angry-Claudius-9B

DeepSeek-V4-Flash-0731-NVFP4-GGUF

Hornybot-Julian-POV

Hornybot-Mara-POV

Moss-image-animated-lora

Moss-image-anime-lora

Moss-image-beauty-lora

Moss-image-gouache-lora

Moss-image-nsfw-uncensored-lora

Moss-image-nsfw-uncensored-lora-GGUF

Moss-image-psychedelic-lora

Moss-Image-SFT-GGUF

暂未找到匹配模型

好模型，也要算好成本。

读懂模型，再做选择

资讯看趋势，工具提效率，模型筑可能。