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Model: noctrex/LFM2.5-8B-A1B-MXFP4_MOE-GGUF
Source: Original Platform

README.md

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+---
+pipeline_tag: text-generation
+base_model:
+- LiquidAI/LFM2.5-8B-A1B
+---
+These are **MXFP4** quantizations of the model [LiquidAI / LFM2.5-8B-A1B](https://huggingface.co/LiquidAI/LFM2.5-8B-A1B)
+
+## Quick Start
+1. Download the latest release of [**llama.cpp**](https://github.com/ggml-org/llama.cpp/releases).
+2. Download your preferred model variant from below.
+
+## Which version should I choose?
+All FP4 variants use **MXFP4** for the MoE (Mixture of Experts) weights to keep the model efficient.  
+I've included also a new type Q8_XL_MOE, that uses Q8_0 for MoE tensors and BF16 for everything else.
+The difference lies in how the remaining tensors are handled:
+
+| Variant            | Quality       | Performance | MoE Tensors | Other Tensors | Size    | Recommendation                                                  |
+| :----------------- | :------------ | :---------- | :---------: | :-----------: | ------: | :-------------------------------------------------------------- |
+| **Q8_XL_MOE**      | ⭐⭐⭐⭐⭐ | Variable\*  |     Q8_0    |     FP16       | 9.02GiB | Maximum quality, uses Q8_0 instead of MXFP4 for the MoE weights. |
+| **MXFP4_MOE_BF16** | ⭐⭐⭐      | Variable\*  |     MXFP4   |     FP16       | 5.18GiB | Best for maximum accuracy; original unquantized weights.         |
+| **MXFP4_MOE_F16**  | ⭐⭐         | Fast       |     MXFP4    |   F16         | 5.18GiB | Great alternative if BF16 is slow on your hardware.             |
+| **MXFP4_MOE**      | ⭐           | Fastest     |    MXFP4    |    Q8_0        | 4.79GiB | Balanced performance and memory usage.                           |
+
+**Note:** On some older architectures, BF16 may be slower than F16.  
+Check that your GPU supports native BF16 acceleration, otherwise it would be better to get the F16 version.
+
+Recommended parameters from LiquidAI:
+- temperature 0.2
+- top_p 80
+- repetition_penalty 1.05
+
+The chat template has been updated to fix the tool calling issues.
+If you don't want to download the model again, you can use the template from the parent model.