How to use from
MLX LM
Generate or start a chat session
# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "mlx-community/gemma-4-E4B-it-qat-assistant-nvfp4"
Run an OpenAI-compatible server
# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "mlx-community/gemma-4-E4B-it-qat-assistant-nvfp4"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "mlx-community/gemma-4-E4B-it-qat-assistant-nvfp4",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'
Quick Links

gemma-4-E4B-it-qat-assistant-nvfp4

This repository contains Multi-Token Prediction (MTP) drafter weights split from google/gemma-4-E4B-it-qat-q4_0-unquantized-assistant for use with mlx-vlm speculative decoding.

This is not a standalone chat or text-generation model. Load it as the draft model alongside a compatible Gemma 4 E4B target checkpoint.

Use with mlx-vlm

uv run mlx_vlm.generate \
  --model google/gemma-4-E4B-it \
  --draft-model mlx-community/gemma-4-E4B-it-qat-assistant-nvfp4 \
  --draft-kind mtp \
  --prompt "Describe this image." \
  --max-tokens 256

For local weights:

uv run mlx_vlm.generate \
  --model /path/to/target-model \
  --draft-model /path/to/gemma-4-E4B-mtp \
  --draft-kind mtp \
  --prompt "Describe this image." \
  --max-tokens 256

Model Details

  • Model type: gemma4_assistant
  • Target architecture: Gemma 4 E4B
  • Precision: nvfp4
  • Runtime: MLX / mlx-vlm
  • Format: Safetensors with MLX-compatible config and tokenizer files

The stored tensors are nvfp4 MLX-compatible drafter weights.

Intended Use

Use this repo only as a speculative decoding drafter for compatible Gemma 4 E4B checkpoints. The target model verifies drafted tokens, while this MTP model proposes candidate tokens per decoding step.

Limitations

This checkpoint requires runtime support for Gemma 4 MTP draft models in mlx-vlm. Standard standalone generation through generic Transformers APIs is not expected to work with this repository by itself.

Please refer to the upstream google/gemma-4-E4B-it model card and license terms for model usage constraints.

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