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It is a LLama 3.1 model, max context of 1 million tokens, with additional steps to improve generation and re-mastered source and ggufs in float 32 (32 bit precision). There are TWO quant sets here, "reg" and "V1.01" (noted in filename). The latter has modifications to address some issues related to non-stop/overly long gen and/or repeat "end paragraph" issues. I am keeping the org quants too, because of the difference in creative generation between the two versions is very strong. I am not saying "reg" is better than "v1.01", they are just different, and you should have the choice between both in my opinion. This model was converted to Nvidia's new "UltraLong8B" long context Llama 3.1 model structure (https://huggingface.co/nvidia/Llama-3.1-8B-UltraLong-1M-Instruct) which allowed full transfer of "Dark Planet 8B" in all it's "glory" so to speak. Due to Nvidia's structure, the new Dark Planet has attained far greater long generation not only in terms of context, but also coherence too. There is a also a bump in overall performance as well.

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It is the new "Llama-3.2-1B-Instruct", max context of 131,000 (128k) with the NEO IMATRIX Science Fiction and Story dataset. The power in this 1B (for its size) is frankly jaw dropping... and at 190 tokens per second + on a GPU. This is a LLAMA 3.2 model, and requires Llama3 template, but may work with other template(s) and has maximum context of 128k.

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It is the new "Llama-3.2-3B-Instruct", max context of 131,000 (128k) with the NEO IMATRIX Science Fiction and Story dataset. The power in this 3B (for its size) is frankly jaw dropping... and at 90 tokens per second + on a GPU. This is a LLAMA 3.2 model, and requires Llama3 template, but may work with other template(s) and has maximum context of 128k.

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It is the new "Llama-3.2-3B-Instruct", max context of 131,000 (128k) with the NEO IMATRIX Tiny "Wee" Horror Dataset. The power in this 3B (for its size) is frankly jaw dropping... and at 90 tokens per second + on a GPU. The NEO IMATRIX dataset V2 was applied to it to enhance creativity (horror). (see several examples below)

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WARNING: NSFW. Vivid prose. INTENSE. Visceral Details. HORROR. Swearing. UNCENSORED... humor, romance, fun. It is a LLama 3.2 model, max context of 128k (131,000) using mixture of experts to combine FOUR top L3.2 3B models into one massive powerhouse at 10B parameters (equal to 12B - 4 X 3 B). This model's instruction following, and output generation for creative writing, prose, fiction and role play are exceptional.

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WARNING: NSFW. Vivid prose. INTENSE. Visceral Details. Light HORROR. Swearing. UNCENSORED... humor, romance, fun. It is a LLama 3.2 model, max context of 128k (131,000) using mixture of experts to combine EIGHT top L3.2 3B models into one massive powerhouse at 18.4B parameters (equal to 24B - 8 X 3B). This model's instruction following, and output generation for creative writing, prose, fiction and role play are exceptional.

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WARNING: NSFW. Vivid prose. INTENSE. Visceral Details. Light HORROR. Swearing. UNCENSORED... humor, romance, fun... and can be used for ANY use case. It is a LLama 3.2 model, max context of 128k (131,000) using mixture of experts to combine EIGHT top L3.2 4B models into one massive powerhouse at 21B parameters (equal to roughly 28B parameters - 8 X 3.75B) with each model infused with Brainstorm 5x to enhance logic and creative performance. This model's instruction following, and output generation for creative writing, prose, fiction and role play are exceptional.

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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。

MODEL HANDBOOK

读懂模型,再做选择

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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