---
type: "Article"
title: "Qwen3.8 27B MLX 4-bit with TensorFold on 1× DGX Spark"
description: "Qwen3.8 27B MLX 4-bit with TensorFold on 1× DGX Spark: recipe by MiaAI-Lab with speed, condition and source for every number, weights and license."
resource: "https://www.contextstudios.ai/local-ai/miaai-lab--qwen3.8-27b-dgx-spark-tensorfold"
language: "en"
generated:
  by: "process:contextstudios-md/1"
  at: "2026-10-23T08:40:00.788Z"
status: "stable"
---

# Qwen3.8 27B MLX 4-bit with TensorFold on 1× DGX Spark

Qwen3.8 27B MLX 4-bit with TensorFold on 1× DGX Spark: 58.3 tok/s according to github.com (dataset as of Sep 29, 2026).

- Creator: [MiaAI-Lab](https://www.contextstudios.ai/local-ai/creators/miaai-lab.md)
- Engine: TensorFold v0.6.0 (c464617) + 5 Patches, Image ghcr.io/miaai-lab/qwen3.8-27b-dgx-spark-tensorfold:v0.6.0, DFlash2-Drafts
- Quantization: MLX affine 4-bit (g64) + FP8 KV, FP8-Prefill
- Model family: Qwen3.8
- Hardware: dgx-spark x1
- Context: 262144
- Artificial Analysis Intelligence Index: 33.7 ([source](https://artificialanalysis.ai/models/qwen3-8-27b))

## All numbers

- 58.3 tok/s (Everyday; Everyday, 1 request, prose prompt, with DFlash2 (per recipe)) — [source](https://github.com/MiaAI-Lab/Qwen3.8-27B-DGX-Spark-TensorFold#performance)
- decode_tps: 58.3 (1 request) — [source](https://github.com/MiaAI-Lab/Qwen3.8-27B-DGX-Spark-TensorFold#performance)
- decode_tps: 323.2 (8 parallel requests) — [source](https://github.com/MiaAI-Lab/Qwen3.8-27B-DGX-Spark-TensorFold#performance)
- prefill_tps: 1793 (1 request) — [source](https://github.com/MiaAI-Lab/Qwen3.8-27B-DGX-Spark-TensorFold#performance)
- ttft_ms: 100 (1 request) — [source](https://github.com/MiaAI-Lab/Qwen3.8-27B-DGX-Spark-TensorFold#performance)

## Weights

- [TensorFold/Qwen3.8-27B-MLX-4bit](https://huggingface.co/TensorFold/Qwen3.8-27B-MLX-4bit) (main, apache-2.0)
- [z-lab/Qwen3.8-27B-DFlash2](https://huggingface.co/z-lab/Qwen3.8-27B-DFlash2) (draft, apache-2.0)
- [Qwen/Qwen3.8-27B](https://huggingface.co/Qwen/Qwen3.8-27B) (base, apache-2.0)

[https://github.com/MiaAI-Lab/Qwen3.8-27B-DGX-Spark-TensorFold](https://github.com/MiaAI-Lab/Qwen3.8-27B-DGX-Spark-TensorFold)

## Related

- [Local AI on your hardware.](https://www.contextstudios.ai/local-ai.md)