---
license: other
license_name: qwen-community-1.0
license_link: LICENSE
library_name: mtplx
pipeline_tag: text-generation
base_model: Qwen/Qwen3.8-Flash-Next
base_model_relation: quantized
tags:
- mtplx
- mlx
- apple-silicon
- macos
- speculative-decoding
- multi-token-prediction
- qwen
- qwen3.8
- qwen3.8-flash-next
- flash-next
- moe
- mtp
- 8-bit
- vision
- mac-studio
---

# Qwen 3.8 Flash-Next Optimized Quality

**The 8-bit build of Qwen 3.8 Flash-Next, for Macs with 256 GB or 512 GB. Requires MTPLX 2.12.0 or later.**

Qwen's 125B-A6B Flash-Next, the Qwen4-generation hybrid mixture of experts with
Qwen Sparse Attention and a 51B-parameter n-gram table, packed for
[MTPLX](https://mtplx.com) with its multi-token prediction head. The main model
and the draft head are 8-bit with group size 64, the structural weights stay in
BF16, and the n-gram table is 4-bit with group size 32. On a Mac with 128 GB or
more, [Optimized Speed](https://huggingface.co/Youssofal/Qwen3.8-Flash-Next-MTPLX-Optimized-Speed) is the
recommended build.

## Memory

The model weights, the draft head and the vision tower need about 128.5 GiB,
and the 32 GB n-gram table streams from SSD.

- **128 GB**: Cannot load. The weights, the draft head and the vision tower alone need about 128.5 GiB.
- **256 GB and 512 GB**: the Macs this pack is for, with about 59.5 GiB left for context and the session cache. The MTPLX app and CLI list it second there, after Optimized Speed.

## Speed

Speed on 256 GB and 512 GB Macs is not measured yet. The 8-bit weights move
twice the bytes per token of Optimized Speed, so expect slower decoding.

## What is in the pack

| Tensor class | Stored precision | Size (GB) |
|---|---|---:|
| attention | Q8/g64 affine; BF16 scales and biases | 0.635044 |
| embeddings | Q8/g64 affine; BF16 scales and biases | 0.675430 |
| gdn A log | BF16 | 0.000003 |
| gdn conv | BF16 | 0.002949 |
| gdn dt bias | BF16 | 0.000003 |
| gdn projections | Q8/g64 affine; BF16 scales and biases | 2.215342 |
| hyper connections | BF16 | 1.279263 |
| lm head | Q8/g64 affine; BF16 scales and biases | 0.675430 |
| mtp attention | Q8/g64 affine; BF16 scales and biases | 0.052920 |
| mtp fc | BF16 | 0.026214 |
| mtp hyper connections | BF16 | 0.039485 |
| mtp norms | BF16 | 0.000089 |
| mtp qsa indexer | Q8/g64 affine; BF16 scales and biases | 0.001741 |
| mtp routed experts | Q8/g64 affine; BF16 scales and biases | 2.673869 |
| mtp router | Q8/g64 affine; BF16 scales and biases | 0.001395 |
| mtp shared expert | Q8/g64 affine; BF16 scales and biases | 0.005222 |
| ngram table | Q4/g32 affine; BF16 scales and biases | 32.000154 |
| norms | BF16 | 0.002076 |
| ple integer buffers | I64 | 0.000000 |
| ple projections and conv | BF16 | 0.065618 |
| qsa indexer | Q8/g64 affine; BF16 scales and biases | 0.020890 |
| routed experts | Q8/g64 affine; BF16 scales and biases | 128.345702 |
| router | Q8/g64 affine; BF16 scales and biases | 0.066977 |
| shared expert | Q8/g64 affine; BF16 scales and biases | 0.250675 |
| vision tower | BF16 | 0.897862 |

The download is 169.96 GB. `size-checksums.json` lists the
size and SHA-256 of every other file.

## Use it

In the Mac app, pick Qwen 3.8 Flash-Next Optimized Quality. From the command line:

```bash
pip install mtplx
mtplx serve --model Youssofal/Qwen3.8-Flash-Next-MTPLX-Optimized-Quality --model-id mtplx-flash-next-optimized-quality
```

MTPLX samples at the official Qwen 3.8 settings (temperature 1.0, top-p 0.95,
top-k 20), and drafts are accepted with exact speculative sampling, so the
output follows the model's own distribution.

Built with the `flash-next-optimized-quality` recipe from
[Qwen/Qwen3.8-Flash-Next](https://huggingface.co/Qwen/Qwen3.8-Flash-Next) at
revision `de4b8e4d43b917e7706784d8bb445c9af86a3540`. Qwen Community License, preserved in
`LICENSE`. The upstream model card is preserved as
`README-upstream-qwen.md`. License and credits are carried from
[Youssofal/Qwen3.8-Flash-Next-MTPLX-Optimized-Speed](https://huggingface.co/Youssofal/Qwen3.8-Flash-Next-MTPLX-Optimized-Speed).
Conversion and serving: MTPLX.