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This repository contains a unified ControlNet for FLUX.1-dev model jointly released by researchers from InstantX Team and Shakker Labs. - This checkpoint is a Pro version of FLUX.1-dev-Controlnet-Union trained with more steps and datasets. - This model supports 7 control modes, including canny (0), tile (1), depth (2), blur (3), pose (4), gray (5), low quality (6). - The recommended controlnet_conditioning_scale is 0.3-0.8. - This model can be jointly used with other ControlNets. Please install `diffusers` from the source, as the PR has not been included in currently released version yet.

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
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来源 / 文档 ↗

This repository contains an unified ControlNet for FLUX.1-dev model released by Shakker Labs. We provide an online demo. A FP8 quantized version provided by community can be found in ABDALLALSWAITI/FLUX.1-dev-ControlNet-Union-Pro-2.0-fp8. In comparison with Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro, - Remove mode embedding, has smaller model size. - Improve on canny and pose, better control and aesthetics. - Add support for soft edge. Remove support for tile. - This ControlNet consists of 6 double blocks and 0 single block. Mode embedding is removed. - We train the model from scratch for 300k steps using a dataset of 20M high-quality general and human images. We train at 512x512 resolution in BFloat16, batch size = 128, learning rate = 2e-5, the guidance is uniformly sampled from [1, 7]. We set the text drop ratio to 0.20. - This model supports multiple control modes, including canny, soft edge, depth, pose, gray. You can use it just as a normal ControlNet. - This model can be jointly used with other ControlNets.

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 ↗
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。

1 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。

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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。

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