MODEL PROFILE · 模型档案

FLUX.1-schnell-GGUF

unsloth · FLUX.1-schnell-GGUF

`FLUX.1 [schnell]` is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. For more information, please read our blog post. 1. Cutting-edge output quality and competitive prompt following, matching the performance of closed source alternatives. 2. Trained using latent adversarial diffusion distillation, `FLUX.1 [schnell]` can generate high-quality images in only 1 to 4 steps. 3. Released under the `apache-2.0` licence, the model can be used for personal, scientific, and commercial purposes. We provide a reference implementation of `FLUX.1 [schnell]`, as well as sampling code, in a dedicated github repository. Developers and creatives looking to build on top of `FLUX.1 [schnell]` are encouraged to use this as a starting point. The FLUX.1 models are also available via API from the following sources - bfl.ml (currently `FLUX.1 [pro]`) - replicate.com - fal.ai - mystic.ai `FLUX.1 [schnell]` is also available in Comfy UI for local inference with a node-based workflow. To use `FLUX.1 [schnell]` with the 🧨 diffusers python library, first install or upgrade diffusers To learn more check out the diffusers documentation --- - This model is not intended or able to provide factual information. - As a statistical model this checkpoint might amplify existing societal biases. - The model may fail to generate output that matches the prompts. - Prompt following is heavily influenced by the prompting-style.

译文排队中,当前展示来源原文。

图像生成license:apache-2.0
上下文窗口来源未披露
输入 → 输出文本 → 图像
模型权重待核验
档案更新时间2026/11/2 19:15:28
OVERVIEW

模型介绍

`FLUX.1 [schnell]` is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. For more information, please read our blog post. 1. Cutting-edge output quality and competitive prompt following, matching the performance of closed source alternatives. 2. Trained using latent adversarial diffusion distillation, `FLUX.1 [schnell]` can generate high-quality images in only 1 to 4 steps. 3. Released under the `apache-2.0` licence, the model can be used for personal, scientific, and commercial purposes. We provide a reference implementation of `FLUX.1 [schnell]`, as well as sampling code, in a dedicated github repository. Developers and creatives looking to build on top of `FLUX.1 [schnell]` are encouraged to use this as a starting point. The FLUX.1 models are also available via API from the following sources - bfl.ml (currently `FLUX.1 [pro]`) - replicate.com - fal.ai - mystic.ai `FLUX.1 [schnell]` is also available in Comfy UI for local inference with a node-based workflow. To use `FLUX.1 [schnell]` with the 🧨 diffusers python library, first install or upgrade diffusers To learn more check out the diffusers documentation --- - This model is not intended or able to provide factual information. - As a statistical model this checkpoint might amplify existing societal biases. - The model may fail to generate output that matches the prompts. - Prompt following is heavily influenced by the prompting-style.

主要特点

特点摘要待依据来源补齐,不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

PRICING & COST

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价,不将渠道价格视为厂商官方统一价格。

来源 / 渠道输入输出计费单位采集时间
暂未取得可核验报价,请查阅来源渠道。

按月估算基础 Token 费用

—

预估不包含缓存优惠、阶梯定价、多模态附加费用、网络检索、税费及推理额外输出。

INDEPENDENT BENCHMARKS

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

查看完整已收录榜单 →

常见问题

开放权重是否代表可以免费商用?

不一定。应核对具体版本许可证、商用门槛和使用政策。自部署还会产生算力和维护成本。

这些价格是实时结算价格吗?

不是实时结算价格,而是带采集时间的来源报价快照。请到对应渠道核对当前版本、区域、折扣和计费方式。

资料来源与可追溯记录

许可证:apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。