--- language: en library_name: mlx tags: - quantized - mlx base_model: XiaomiMiMo/MiMo-V2.5 base_model_relation: quantized pipeline_tag: text-generation --- **See MiMo-V2.5 in action - [demonstration videos](https://youtube.com/xcreate)** #### Tested on a M3 Ultra 512GB RAM using [Inferencer app v1.11.1](https://inferencer.com) - Text inference: ~32.8 tokens/s @ 1000 tokens (debug build) - Omnimodal inference: Not included in this language model (LM) only version - Memory usage: ~209 GiB 
Q5.8-INF uses the data-agnostic INF method tuned to yield maximum general accuracy within a 256 GiB memory budget The perplexity results below show the loss relative to the Q9 edition on our coding test.
| Quantization (bpw) | Perplexity | Token Accuracy | Missed Divergence | Size |
|---|---|---|---|---|
| Q5.5 | 1.07812 | 98.25% | 11.45% | 212.35 GB |
| Q5.8-INF | 1.07031 | 99.30% | 10.81% | 225.03 GB |
| Q6.5 | 1.07812 | 99.15% | 0.05% | 250.94 GB |
| Q9 (Base) | 1.07031 | 100.00% | 100.00% | 347.43 GB |