---
license: apache-2.0
base_model: tencent/Hy3
library_name: mlx
pipeline_tag: text-generation
language: en
tags:
  - mlx
  - apple-silicon
  - hy3
  - mixture-of-experts
  - mtp
  - speculative-decoding
  - mtplx
---

# Hy3-Demolition-MLX reap25-v1-mtp

[Explore the model guide](https://huggingface.co/spaces/philipjohnbasile/local-ai-guide) · [All public work](https://huggingface.co/philipjohnbasile)

## Release at a glance

| | This artifact |
|---|---|
| Purpose | The REAP25 trunk with a draft sidecar whose expert axis was reduced to match the 144-expert trunk. |
| Runtime | Requires a compatible Hy3 implementation and MTPLX MTP contract. Structural recognition is separate from generation qualification. |
| Status | Runtime verification pending; see the evidence and limits below. |
| Tensor download | 86.89 GB (80.92 GiB) of root `.safetensors` files, including any root sidecars. This is a file-size total, not peak RAM. |
| Read first | Draft-head modification can change acceptance; output equivalence depends on a correctly implemented and verified decoding path. |

The **MTP-equipped** variant of [reap25](https://huggingface.co/philipjohnbasile/hy3-demolition-mlx-reap25-v1): its fused trunk with the Hy3 **NextN (Multi-Token-Prediction) sidecar** grafted back on (`num_nextn_predict_layers=1`, num_experts=144), for self-speculative decoding on MTPLX.

## Runtime status — reviewed September 10, 2026

The original `recognized-backend-pending` observation came from MTPLX
2.0.1. It is historical: the maintainer subsequently confirmed that the
Hy3 and Qwen MTP backend work shipped in 2.1.0 through the release branch.
[Read the upstream shipping record](https://github.com/youssofal/MTPLX/pull/142).

That code shipment does not qualify this exact checkpoint. The source
Hy3 implementation, runtime contract, loading, output agreement, and
performance still need to be checked together. No fresh end-to-end MTP
qualification of this artifact is claimed here. Upstream mlx-lm PR
[#1211](https://github.com/ml-explore/mlx-lm/pull/1211) remained open at review.

The documented AR path is the [sibling model](https://huggingface.co/philipjohnbasile/hy3-demolition-mlx-reap25-v1).

## How it was built

The MTP head consumes the trunk's final hidden state (hidden_size 4096, unchanged by pruning) and runs its own MoE on the global `num_experts`. So the base checkpoint's `mtp.*` sidecar grafts directly onto the fused AR trunk — no re-heal, no re-prune of the trunk.
- The MTP head's experts are sliced 192→144 (packing-safe whole-expert axis slice, scales-L2 pick) to match the pruned trunk's `num_experts`. The MTP head is a *draft* component MTPLX verifies every token against, so this changes the draft proposal distribution. Output equivalence requires a correctly implemented and validated verification path; it is not established by grafting the head.

Graft script + `mtplx inspect` receipts: https://github.com/PhilipJohnBasile/hy3-demolition-mlx (`scripts/38_mtp_sidecar_graft.py`, `eval/receipts/mtplx_inspect_*.json`).

## Limitations

- **Does not run on stock mlx_lm as MTP.** The fast MTP path needs the MTPLX backend; mlx-lm's own per-token self-speculative loop is ~4.7× *slower* than AR (measured), which is why the MTPLX batched-verify backend is the target.
- Everything from the base reap25 card applies (quantized MoE, English/agent focus, no tool execution).
- End-to-end MTP behavior is **unverified** until the backend loads it; recognition is structural (`mtplx inspect`), not a live run.

Base recipe + receipts: https://github.com/PhilipJohnBasile/hy3-demolition-mlx

## Other serving applications

No current LM Studio or Ollama qualification of this artifact is recorded
here. An architecture becoming available in one library does not establish
support in every application. Use the AR sibling's pinned release recipe
as the documented starting point.

## Experimental streaming

The source project's SSD pager measurements concern an AR serving path.
They do not qualify this MTP variant on a smaller-memory machine.
[Read the AR streaming experiment](https://github.com/PhilipJohnBasile/hy3-demolition-mlx/blob/main/docs/64gb-feasibility.md).