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NexoNimbus-MoE-2x7B-GGUF

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GGUF
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Mixture of Experts
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abideen/NexoNimbus-7B
mlabonne/NeuralMarcoro14-7B
Inference Endpoints
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@@ -39,14 +39,13 @@ more details, including on how to concatenate multi-part files.
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.IQ4_XS.gguf) | IQ4_XS | 7.2 | |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q4_0.gguf) | Q4_0 | 7.5 | fast, low quality |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q4_K_S.gguf) | Q4_K_S | 7.6 | fast, recommended |
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- | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.IQ4_NL.gguf) | IQ4_NL | 7.6 | slightly worse than Q4_K_S |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q4_K_M.gguf) | Q4_K_M | 8.0 | fast, recommended |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q5_K_S.gguf) | Q5_K_S | 9.1 | |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q5_K_M.gguf) | Q5_K_M | 9.4 | |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q6_K.gguf) | Q6_K | 10.8 | very good quality |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q8_0.gguf) | Q8_0 | 13.9 | fast, best quality |
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-
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  Here is a handy graph by ikawrakow comparing some lower-quality quant
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  types (lower is better):
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.IQ4_XS.gguf) | IQ4_XS | 7.2 | |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q4_0.gguf) | Q4_0 | 7.5 | fast, low quality |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q4_K_S.gguf) | Q4_K_S | 7.6 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.IQ4_NL.gguf) | IQ4_NL | 7.6 | prefer IQ4_XS |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q4_K_M.gguf) | Q4_K_M | 8.0 | fast, recommended |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q5_K_S.gguf) | Q5_K_S | 9.1 | |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q5_K_M.gguf) | Q5_K_M | 9.4 | |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q6_K.gguf) | Q6_K | 10.8 | very good quality |
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  | [GGUF](https://huggingface.co/mradermacher/NexoNimbus-MoE-2x7B-GGUF/resolve/main/NexoNimbus-MoE-2x7B.Q8_0.gguf) | Q8_0 | 13.9 | fast, best quality |
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  Here is a handy graph by ikawrakow comparing some lower-quality quant
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  types (lower is better):
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