mavis-ai/Gemma4-26B-MoE-Q4

This model is a mixed-policy 4-bit MLX quantized version of the official Google Gemma 4 26B model. No structural modifications or fine-tuning have been applied to the base weights; the package applies MLX quantization while preserving the higher-precision tensor groups indicated by Google's official QAT Q4 GGUF layout.

💡 Notice for Everyone While this repository is hosted primarily as a dedicated engine source for our application ecosystem (R.E.V.I.S.), you are completely free to download and use this quantized model normally for your own local MLX projects or workflows. For more details on the base model, please refer directly to the Official google/gemma-4-26B-A4B page.

🚀 Optimized for R.E.V.I.S. (Local Cognitive OS)

We quantized and thoroughly tested this model to serve as the local reasoning engine for our project: R.E.V.I.S. (Note: This specific Q4 model is exactly what we used in our official launch demo!)

R.E.V.I.S. is a 100% local Cognitive OS for Multi-Agentic AI. It transforms your Mac devices into a distributed Agentic Swarm via zero-config Wi-Fi clustering, allowing you to run heavy AI workloads—like recursive web research, dynamic RAG generation, and multi-step logic—without killing single-machine performance.

If you are interested in pushing the absolute limits of local AI and open-weight models like this one, check out our project!

Quantization

This package follows the quantization boundaries used by Google's official Gemma 4 QAT Q4 GGUF release, adapted for a regular Q4 build:

  • Default language tensor quantization: MLX affine Q4
  • Token embeddings: MLX affine Q6
  • Shared MLP and expert tensors: MLX affine Q4
  • Router projection and router scale tensors: BF16
  • Vision and multimodal projection components: BF16
  • Group size: 64
  • Mode: affine

License

This model is a quantized derivative of Google's Gemma 4 (base model: google/gemma-4-26B-A4B), which is released by Google under the Apache License 2.0.

This derivative is likewise distributed under the Apache License 2.0. A copy of the license is included in the LICENSE file in this repository, and can also be found at https://www.apache.org/licenses/LICENSE-2.0.

Modification notice: The base weights have been converted to MLX and quantized with a mixed Q4/Q6/BF16 policy. No fine-tuning or structural modifications were made to the model architecture.

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