best-from-civitai
Quiho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。
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。
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。
基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
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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。
These are some XL models based on NoobAI/pony XL with a little modifications, they are mainly for anime/realistic bara kemono content, and should be ok for all contents. I chose pony purely because of its NSFW ability. (Now I'm thinking about switching to NoobXL because Pony is a pain in the ass to tweak) NoobAI based model out now. If you like my work, consider buy me a coffee please <3 (completely voluntary) \u5982\u540cLicense\u5185\u63d0\u53ca\u7684\uff0c\u672c\u6a21\u578b\u53ca\u5176\u751f\u6210\u7684\u56fe\u50cf\u7981\u6b62\u5546\u4e1a\u5316\u4f7f\u7528\uff01 For CkNoob_EPS_\u216a_11: This is a new EPS model that based on Chenkin Noob v0.1. Based on my testing, compared to EPS10, this model features better background coherence, higher contrast, slightly more detail, and a bit more responsiveness to artist styles. Just note that the composition of the generated images with the same prompt can sometimes differ noticeably from EPS10. And the overall feel and behavior of this model can sometimes differ from EPS10. Just as the EPS10, when using this model, try using a CFG scale between 3\u20137 (recommended 5). It is recommended to keep using Euler a sampler for best overall results, but switching to DPM++ 2M may produce more detailed (and chaotic) outputs. For NoobAI_EPS_\u2169_10: This is a new EPS model that merges the the core features (hopefully) of EPS3 and EPS7. It aims to increase overall versatility while sacrificing just bit of fine detail. Backgrounds are much more stable compared to EPS3, though occasionally not as consistent as EPS7. EPS10 fixed the issue of overly saturated or blown-out colors at high CFG values. Artist tags still work well as before, and stability when using the DPM++ 2M sampler has been improved. When using this model, try using a CFG scale between 3\u20137 (recommended 5). It is recommended to keep using Euler a sampler for best overall results, but switching to DPM++ 2M may produce more detailed (chaotic) outputs.
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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。
This is a dedicated rank-64 LoRA trained with one narrow objective: reduce Krea2\u2019s learned refusal and restriction behavior while preserving as much of the base model\u2019s existing visual knowledge and prompt behavior as possible. This is not a concept, character, style, anatomy, or aesthetic LoRA. It was not trained to add new visual concepts, reproduce a training-image set, or impose a preferred look. Its training objective was exclusively to push the model away from refusal behavior so that concepts already represented within the base model are less likely to be suppressed during text conditioning. Krea2 receives multiple hidden-state taps from its Qwen-VL text encoder and processes them through TextFusion before sending the resulting conditioning into the image transformer. This LoRA applies learned low-rank residuals only to the attention and internal MLP projections within: - txtfusion.layerwise_blocks.0 - txtfusion.layerwise_blocks.1 - txtfusion.refiner_blocks.0 - txtfusion.refiner_blocks.1 The release version deliberately contains no adapter for: - The TextFusion 1 \u00d7 12 tap projector - The external/general txtmlp - The image-transformer blocks or any other image-generation layers The base checkpoint is never overwritten. For every targeted linear layer, LoRA adds a learned rank-64 residual to the original weight during inference: W_effective = W_base + strength \u00d7 \u0394W This changes how existing Qwen-VL text features are routed, gated, transported, and refined through TextFusion before they reach Krea2\u2019s untouched image transformer. In other words, the LoRA is intended to improve access to visual knowledge already present in the base model, not inject a new concept or replace the model\u2019s learned visual representations. This release targets the specific TextFusion route isolated through layer-by-layer ablation instead of broadly amplifying activations or directly alte...
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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。
基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
UPDATED 8/22/2026 - Announcing Krea 2 Turbo Edit v1.1 GGUF and FP8 an all new updated version with bug fixes and major improvements. 1. **Fine Detail LoRA** - Sharpens and refines facial features and "sensitive" parts. (0.75 strength.) 2. **Identity Edit LoRA** - Strong edits and identity preservation. (1.0 strength) 3. **4-step Turbo LoRA** - The latest 4-step rank-64 lora that reduces the minimum usable step count from 8 to 4. (1.0 strength) 4. **Skin Detail LoRA** - Skin refiner to remove the "plastic" look (0.45 strength) 5. **Refusal Reduction NSFW LoRA** - The latest NSFW rank-64 lora to supress restrictions. (0.8 strength) Original Prompt: Edit this picture. She is wearing a bikini only. Keep the shirt on the bunny that says "Krea2". Soft studio lighting, white background, 3/4 body shot.
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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。
基本情報を収録・詳細は順次追加
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。
基本情報を収録・詳細は順次追加
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。