Add vMLX model card

README.md

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+---
+language:
+- en
+license: apache-2.0
+pipeline_tag: text-generation
+tags:
+- mlx
+- mixture-of-experts
+- moe
+- pruning
+- reap
+- step3p5
+- mixed-quantization
+- apple-silicon
+library_name: mlx
+base_model: lkevincc0/Step-3.5-Flash-REAP-128B-A11B
+---
+
+<p align="center">
+  <a href="https://vmlx.net">
+    <img src="vmlx-logo.png" alt="vMLX" width="120">
+  </a>
+</p>
+
+# Step-3.5-Flash REAP 128B-A11B — MLX Mixed 4/6-bit
+
+MLX mixed-precision quantized version of [lkevincc0/Step-3.5-Flash-REAP-128B-A11B](https://huggingface.co/lkevincc0/Step-3.5-Flash-REAP-128B-A11B) for efficient local inference on Apple Silicon.
+
+- **Quantization**: Mixed 4/6-bit — v_proj and down_proj at 6-bit, all other weights at 4-bit (group size 64, affine mode)
+- **Architecture**: Step-3.5 SMoE — 45 layers, 173 routed experts (REAP-pruned), 8 active per token, shared expert
+- **Parameters**: 128B total, 11B active per token
+- **Context**: 262K tokens
+- **Size**: ~68 GB
+- **Pruning**: ~40% of experts removed via [REAP](https://github.com/CerebrasResearch/reap) (Router Expert Activation Pruning)
+
+## Usage
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("shieldstackllc/Step-3.5-Flash-REAP-128B-A11B-mlx-mixed-4-6")
+response = generate(model, tokenizer, prompt="Hello!", verbose=True)
+```
+
+Or with [vMLX](https://vmlx.net) for native macOS inference.
+
+## About
+
+Step-3.5-Flash is a large Mixture-of-Experts language model by [StepFun AI](https://stepfun.com). This variant was pruned by [lkevincc0](https://huggingface.co/lkevincc0) using REAP (Router Expert Activation Pruning), reducing the expert count from the original to 173 while maintaining strong performance. The mixed-precision MLX quantization preserves higher fidelity on critical attention and feed-forward projections by using 6-bit for v_proj and down_proj layers.
+
+## Made for vMLX
+
+This model was converted and optimized for [vMLX](https://vmlx.net) — a free, open source macOS native MLX inference engine for Apple Silicon. Download vMLX to run this model locally with zero configuration.
+
+## Credits
+
+- **Base model**: [stepfun-ai/Step-3.5-Flash](https://huggingface.co/stepfun-ai/Step-3.5-Flash) by StepFun AI
+- **REAP pruning**: [lkevincc0/Step-3.5-Flash-REAP-128B-A11B](https://huggingface.co/lkevincc0/Step-3.5-Flash-REAP-128B-A11B) by lkevincc0
+- **MLX conversion**: [vMLX](https://vmlx.net) — Run AI locally on Mac. No compromises.
+
+## Contact
+
+For questions, issues, or collaboration: **admin@vmlx.net**