gemma-4-31B-it-INT8
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从语言到影像,从开源到 API。读懂模型能力、比较真实成本,
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Two accepted weight-only releases are available for the H3 Beta7 transformer from TenStrip/10Eros-Max. Both retain the source's embedded eight-step Turbo. **HQ (18.69 GB) remains the recommended choice for quality**, using learned W6 g16 and INT8 ConvRot weights. **Compact (14.65 GB)** adds W4 g16 to reduce the weight footprint for setups with less available memory. Both passed mechanical validation and operator ComfyUI acceptance on **2026-10-28**. For compact, the operator reports slightly lower quality than HQ while holding up well, with lower observed memory use. These are qualitative observations without measured VRAM savings or a controlled quality score. The older Beta6 compact remains a separate source release. Beta7 has the standard H3 tensor layout without compression-gate tensors. The upstream author describes its merge as MLP-focused, preserving base attention/reference behavior, and recommends Euler/simple or ER-SDE/SGM_uniform for its Turbo sampling. See the upstream source notes for its recipe, workflow settings and known limitations.
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The goal of this project is to improve generation of moe characters since most of other models are not good at it. \ \ __Some of the models can be used online on these plarforms:__ \ __Aipictors (Japanese) - https://www.aipictors.com__ It is recommende to use standard resolution such as 832x1144 \ Positive prompt example: masterpiece, best quality, 1girl, solo, full body, night, purple kimono, japanese clothes, barefoot, obi, bare legs, braided ponytail, feet, mole, toes, collarbone, toenails, electricity, looking at viewer, night sky, holding weapon, holding, holding polearm, floating, sakura, petals \ Negative prompt example: lowres, worst quality, low quality, old, early, bad anatomy, bad hands, 4koma, comic, greyscale, censored, jpeg artifacts, monochrome, simple background, \ All examples were generated using custom workflow in ComfyUI and weren't edited using inpainting. You can load the workflow by either importing the example images or importing the workflow directly v3.0 \ Anima v1 based \ Better anatomy, smaller model, better prompt adherance \ Use @artist for artists, case sensitive \ You can use both tags and natural language prompts and you will likely achieve better results combining both \ It's better to use longer prompts for better results, shorter (sub 10 tags) may result in lower quality \ Use er_sde sampler and simple or maybe beta scheduler, cfg around 4 maybe even closer to 3 v0.4.3 \ Fixed color issue \ General improvements \ \ v0.5.3 \ Integrated VAE\ File size reduced \ CLIP force reset fix \ \ v0.6.3 \ Style improvements \ Added PastelMix and Counterfeit style \ \ v0.7.x \ Style impovements \ Composition improvements \ \ v0.8.x \ Major improvement on higher resolutions \ Style improvements \ Flexibility and responsivity \ Added support for Night Sky YOZORA model \ \ v0.9.x \ Different approach at merging, you might find v0.8.x versions better \ Changes at supported models \ \ v2.1.X EXPERIMENTAL RELEASE \ Stable Diffusion 2.1-768 based \ Default negative prompt: (low quality, worst quality:1.4), (bad anatomy), extra finger, fewer digits, jpeg artifacts \ For positive prompt it's good to include tags: anime, (masterpiece, best quality) alternatively you may achieve positive response with: (exceptional, best aesthetic, new, newest, best quality, masterpiece, extremely detailed, anime, waifu:1.2) \ Though it's Loli Diffusion model it's
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可以调整厂商、分类或输入输出条件;新模型正持续收录。
调整月度 Token 用量,直观比较不同模型的预估 API 开支。
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。
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。
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。
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。