qwen-image-edit-gguf
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言語から画像、オープンウェイトからAPIまで。能力と実際の費用を比較。
次のアイデアに合うAIを見つけましょう。
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The **FLUX Uncensored LoRA v2** is an enhanced version of the original FLUX Uncensored LoRA, designed for the base model `black-forest-labs/FLUX.1-dev`. This version addresses issues present in the previous release and offers improved performance and stability. The LoRA weights have been fine-tuned to remove the base model's content restrictions, allowing for the generation of NSFW (Not Safe For Work) and other uncensored content. This LoRA extension can be loaded into the `FLUX.1-dev` pipeline using the `diffusers` library. It is optimized for high-quality, explicit image generation based on user-provided prompts. The model is intended for research and personal use, and adheres to the non-commercial license terms. > **Warning:** This model allows the generation of explicit content. Users should exercise caution and adhere to legal and ethical guidelines.
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`FLUX.2 [dev]` is a 32 billion parameter rectified flow transformer capable of generating, editing and combining images based on text instructions. For more information, please read our blog post. This repository holds an NVFP4 version and a mixed NVFP4/BF16 version of FLUX.2 [dev]. The mixed version has a small set of weights in BF16. The main repository of this model (full BF16 weights) can be found here.
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The FLUX.2 [klein] model family are our fastest image models to date. FLUX.2 [klein] unifies generation and editing in a single compact architecture, **delivering state-of-the-art quality with end-to-end inference in as low as under a second**. Built for applications that require real-time image generation without sacrificing quality, and runs on consumer hardware, with as little as 13GB VRAM. FLUX.2 [klein] 4B is a 4 billion parameter rectified flow transformer capable of generating images from text descriptions and supports multi-reference editing capabilities. Fully open under Apache 2.0. Our most accessible model runs on consumer GPUs like the RTX 3090/4070. Compact but capable: supports text-to-image, image editing, and multi-reference at quality that punches above its size. Built for local development, edge deployment, and production use.
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`FLUX.2 [klein] 4B` is a 4 billion parameter rectified flow transformer capable of generating images from text descriptions and supports multi-reference editing capabilities. For more information, please read our blog post. This repository holds an FP8 version of FLUX.2 [klein] 4B. The main repository of this model (full BF16 weights) can be found here. - This model is not intended or able to provide factual information. - While the model can output text, text rendered may be inaccurate or subject to distortion. - As a statistical model, this checkpoint may represent or amplify biases observed in the training data. - The model may fail to generate output that matches the prompts. - Prompt following is heavily influenced by the prompting style.
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`FLUX.2 [klein] 4B` is a 4 billion parameter rectified flow transformer capable of generating images from text descriptions and supports multi-reference editing capabilities. For more information, please read our blog post. This repository holds an NVFP4 version of FLUX.2 [klein] 4B. The main repository of this model (full BF16 weights) can be found here. Nothing contained in this Model Card should be interpreted as or deemed a restriction or modification to the license the model is released under.
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`FLUX.2 [klein] 9B-KV` is an optimized variant of FLUX.2 [klein] 9B with **KV-cache support for accelerated multi-reference editing**. This variant caches key-value pairs from reference images during the first denoising step, eliminating redundant computation in subsequent steps for significantly faster multi-image editing workflows. For more information about FLUX.2 [klein], please read our blog post. 1. **KV-Cache Optimization**: Reference image KV pairs are computed once and cached, reducing computation and speeding up inference by up to 2.5 times for multi-reference editing tasks. 2. All capabilities of FLUX.2 [klein] 9B: sub-second generation, text-to-image, and multi-reference editing in a single unified model. 3. Ideal for interactive applications and real-time editing pipelines where the same reference images are used across multiple generations. 4. 9B flow model with 8B Qwen3 text embedder, step-distilled to 4 inference steps. 5. Available for non-commercial use.
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The FLUX.2 [klein] model family are our fastest image models to date. FLUX.2 [klein] unifies generation and editing in a single compact architecture, **delivering state-of-the-art quality with end-to-end inference in as low as under a second**. Built for applications that require real-time image generation without sacrificing quality, and runs on consumer hardware, with as little as 13GB VRAM. FLUX.2 [klein] 4B Base is a 4 billion parameter rectified flow transformer capable of generating images from text descriptions and supports multi-reference editing capabilities. It's a full-capacity foundation model. Undistilled, preserving complete training signal for maximum flexibility. Ideal for fine-tuning, LoRA training, research, and custom pipelines where control matters more than speed. Higher output diversity than the distilled models.
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`FLUX.2 [klein] 4B Base` is a 4 billion parameter rectified flow transformer capable of generating images from text descriptions and supports multi-reference editing capabilities. For more information, please read our blog post. This repository holds an FP8 version of FLUX.2 [klein] 4B Base. The main repository of this model (full BF16 weights) can be found here. - This model is not intended or able to provide factual information. - While the model can output text, text rendered may be inaccurate or subject to distortion. - As a statistical model, this checkpoint may represent or amplify biases observed in the training data. - The model may fail to generate output that matches the prompts. - Prompt following is heavily influenced by the prompting style.
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`FLUX.2 Small Decoder` is a distilled VAE decoder that serves as a **drop-in replacement** for the standard FLUX.2 decoder. It delivers faster decoding and lower VRAM usage with minimal to zero quality loss. The encoder remains unchanged. 1. **~1.4x faster decoding** compared to the full decoder. 2. **~1.4x less VRAM** at decode time, enabling higher resolutions without running out of memory. 3. **~28M decoder parameters** (vs ~50M in the full decoder) thanks to narrower channel widths (`[96, 192, 384, 384]` vs `[128, 256, 512, 512]`). 4. **Minimal quality loss** — images are almost identical. 5. Available under the Apache 2.0 license. Compatible with all open FLUX.2 models: - FLUX.2-klein-4B - FLUX.2-klein-9B - FLUX.2-klein-9b-kv - FLUX.2-dev
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FLUX 3 Image Klein API:Black Forest Labs 开放权重图像模型(5.6B 参数),支持文生图、指令编辑与多图参考,最多 10 张参考图;提供 768sq 至 4k 五档分辨率与 15 种宽高比,并可设置随机种子、1–16 步降噪及 PNG/JPEG 输出,在 APIMart 调用。
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提供元・分類・入出力の条件を変更してください。新しいモデルを随時追加しています。
月間トークン数を調整してAPI費用を比較。
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。
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。
必ずしもそうではありません。バージョンごとのライセンス、商用制限、ポリシーを確認してください。自前運用には計算資源と保守費用も必要です。
順位はテスト、バージョン、評価方法によります。実際の業務データで精度、遅延、安定性、費用を比較してください。