---
base_model: deepgrove/maple-preview
base_model_relation: quantized
language:
  - en
library_name: onnxruntime
license: mit
pipeline_tag: text-generation
tags:
  - onnx
  - onnxruntime
  - android
  - maple
  - mixture-of-experts
  - quantized
  - openmed
---

# Maple Preview 4-bit ONNX for Android

Private OpenMed development export of
[`deepgrove/maple-preview`](https://huggingface.co/deepgrove/maple-preview)
revision `ac1ddd79d2b5cb4406f5d2bebdf95406ce505a07` for ONNX Runtime Mobile.
The expert matrices use symmetric 4-bit, 128-value blocks through the fused
`com.microsoft.QMoE` operator. Router computation and the public graph I/O use
FP32. The included `openmed-maple-onnx-export.json` is the integrity receipt
for every file, source revision, conversion dependency, and validation gate.

## Validation status

The complete 24-layer graph passed ONNX checker and OpenMed's graph contract.
On ONNX Runtime 1.25.1 CPU it completed a real one-token prefill and cached
decode with finite logits and KV growth from one to two tokens. The exact fused
QMoE form also passes the standalone operator smoke test.

Source-logit parity, useful generation, direct-identifier recall,
critical-leakage, peak memory, latency, and physical Android execution remain
release gates. This is conversion and CPU-runtime evidence only.

## Integration

The cache contract, bundle validator, and Compose demo are documented in
[`docs/maple-on-device.md`](https://github.com/maziyarpanahi/openmed/blob/master/docs/maple-on-device.md).
Applications must verify the receipt's sizes and SHA-256 digests before moving
the selected model into protected app storage. Do not add cloud fallback for
PHI workflows.

Maple Preview is a research model, not a medical device. It must not
automatically trigger clinical or disclosure decisions. The upstream model is
licensed under MIT; see its repository for the license and model card.