Youssofal/Qwen3.8-Flash-Next-MTPLX-Optimized-Speed
[MTPLX](https://mtplx.com): the fastest way to run Qwen 3.8 on a Mac. Native multi-token-prediction speculative decoding on Apple Silicon, two to three times the speed of plain decoding, exact at any temperature.
Qwen 3.8 Flash-Next Optimized Speed
Dynamic 4-bit quant with 8-bit attention. Higher quality and slightly slower. Recommended.
Qwen's 125B-A6B Flash-Next preview, the Qwen4-generation architecture with GDN hybrid MoE, Qwen Sparse Attention, and the 51B-parameter n-gram memory, running natively on MTPLX from day 0, with its native multi-token-prediction head drafting through MTPLX's speculative path. This is the recommended build: the Qwen Sparse Attention projections are kept at 8-bit, so the attention pathway that steers long contexts keeps its precision. For the absolute fastest build, pick Bare Speed.
The 32 GB n-gram table streams from SSD, so only the weights stay in memory. The pack peaks at 87 GiB while serving, so it is recommended for Macs with 128 GB or more. On a 96 GB Mac, use Bare Speed, which peaks at 78 GiB.
Measured on MTPLX 2.11.3 (16 September 2026)
This is the Qwen3.8-Flash-Next MLX pack for MTPLX, the fastest way to run Qwen 3.8 Flash Next on a Mac. MacBook Pro M5 Max with 128 GB, fans verified at maximum, sampled at the model's own settings (temperature 1.0, top-p 0.95, top-k 20). Conditions and sources for every row: mtplx.com/benchmarks.
Exactness on this release: a thousand four-token draws from the fast path match a thousand from the plain path within the plain path's own noise at every joint length, at temperature 1, top-p 0.95, top-k 20. A 96,760-token conversation restored from the session cache in 8 ms. 261,120-token prompts decode. Details: MTPLX 2.11.3 release notes.
Recommended for Apple Silicon Macs with 128 GB of unified memory or more: MacBook Pro M4 Max and M5 Max with 128 GB, and Mac Studio M3 Ultra, M4 Max and M5 Max with 128 GB or more. From MTPLX 2.12.0 it is the first recommendation on Macs with 256 GB or more. Guide: Run Qwen 3.8 Flash Next on a Mac.
Speeds
Measured on an M5 Max, fans verified at max, single stream, real server (mtplx serve), official Qwen 3.8 sampling (temperature 1.0, top-p 0.95, top-k 20, sampled, not greedy).
That is a 1.7x speculative multiplier through the product serve path, on sampled output that follows the model's own distribution.
How it is built
- MoE experts and dense matrices at 4-bit with 64-weight groups; the Qwen Sparse Attention projections promoted to 8-bit (the quality edge over Bare Speed).
- The GDN convolution and recurrent-state parameters, every norm, the QSA indexer, and the MTP head stay 16-bit.
- The n-gram embedding table ships as a separate
ngram-table.safetensorssidecar that MTPLX streams from SSD on every Mac. The vision tower is preserved in the weights.
The serving contract ships inside mtplx_runtime.json. MTPLX reads it on load. Drafts are accepted with the probability-ratio rule plus residual resampling, so the output follows the model's own distribution at any temperature.
Use it
Mac app: download at mtplx.com, pick "Qwen 3.8 Flash-Next Optimized Speed".
Command line:
pip install mtplx
mtplx serve --model Youssofal/Qwen3.8-Flash-Next-MTPLX-Optimized-SpeedSibling: Bare Speed (flat 4-bit, the quickest build).
Base model: Qwen/Qwen3.8-Flash-Next (Qwen Community License; the upstream model card is preserved in this repo as README-upstream-qwen.md).