---
title: Muse-Spark-Open-816B-A42B-oQ3e
canonical_url: "https://www.modelscope.cn/models/mlx-community/Muse-Spark-Open-816B-A42B-oQ3e"
md_url: "https://www.modelscope.cn/models/mlx-community/Muse-Spark-Open-816B-A42B-oQ3e.md"
repository: mlx-community/Muse-Spark-Open-816B-A42B-oQ3e
last_updated: 2026-10-16
license: other
pipeline_tag: image-text-to-text
tasks:
  - image-text-to-text
model_type:
  - muse_spark
architectures:
  - MuseSparkForConditionalGeneration
base_model:
  - meta-models/Muse-Spark-Open-816B-A42B
base_model_relation: quantized
parameters: 77.2B
tensor_type:
  - BF16
  - U32
  - F32
library_name:
  - mlx
  - safetensors
  - pytorch
frameworks:
  - pytorch
downloads: 129
stars: 0
tags:
  - mlx
  - oq
  - quantized
  - muse
  - muse-spark
---

# Muse-Spark-Open-816B-A42B-oQ3e

> Muse-Spark-Open-816B-A42B-oQ3e - mlx-community 在 ModelScope 开源的模型。Muse-Spark-Open-816B-A42B-oQ3e

mlx-community/Muse-Spark-Open-816B-A42B-oQ3e 是 ModelScope 魔搭社区上的 77.2B 参数image-text-to-text模型，采用 other 许可，基于 meta-models/Muse-Spark-Open-816B-A42B 构建。

- **Repository**: mlx-community/Muse-Spark-Open-816B-A42B-oQ3e
- **License**: other
- **Tasks**: image-text-to-text
- **Parameters**: 77.2B
- **Base model**: meta-models/Muse-Spark-Open-816B-A42B
- **Tags**: mlx, oq, quantized, muse, muse-spark
- **Downloads**: 129
- **Stars**: 0
- **Last updated**: 2026-10-16

Source: https://www.modelscope.cn/models/mlx-community/Muse-Spark-Open-816B-A42B-oQ3e

---

# Muse-Spark-Open-816B-A42B-oQ3e

This model was quantized using [oQ](https://github.com/jundot/omlx) (oMLX v0.7.1) mixed-precision quantization with oQe importance-matrix quantization.

Re-uploaded on 2026-10-16 at 08:19 UTC in the layout of mlx-lm 0.32.2, so it loads in both mlx-lm 0.32.2 and oMLX. This version keeps the lm_head in BF16, which mlx-lm 0.32.2 needs for this model, and gives q, k, v and the attention output gate of each layer one bit width, as mlx-lm stores them as one projection.

A mixed-precision MLX checkpoint of [meta-models/Muse-Spark-Open-816B-A42B](https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B), Meta's 816B total / 42B active Mixture-of-Experts model with a 1M-token context window, built for coding and agentic work. It includes the language model and the vision encoder. The audio encoder is not included.

The effective average is 3.616 bits/weight for the complete checkpoint.

## Quantization and Bit Distribution

oQ3e allocates bits by measured layer sensitivity, then rounds each group with an importance matrix (128 samples x 512 tokens) and a weighted least-squares refit of its scale and bias.

| Storage format | Logical weights | Share of total | Tensor storage | Effective bits/weight |
|---|---|---|---|---|
| Affine 3-bit, group 64 | 798.864B | 97.195% | 325.500 GiB | 3.50 |
| Affine 5-bit, group 64 | 8.338B | 1.014% | 5.339 GiB | 5.50 |
| Affine 4-bit, group 64 | 6.275B | 0.763% | 3.287 GiB | 4.50 |
| Affine 8-bit, group 64 | 4.725B | 0.575% | 4.676 GiB | 8.50 |
| BF16 | 3.585B | 0.436% | 6.678 GiB | 16.00 |
| FP32 | 0.132B | 0.016% | 0.492 GiB | 32.00 |
| **Total** | **821.920B** | **100%** | **345.972 GiB** | **3.616** |

## Storage Breakdown

| Component | Logical weights | Storage |
|---|---|---|
| Language backbone | 819.992B | 367.628 GB / 342.381 GiB |
| Vision encoder | 1.928B | 3.856 GB / 3.591 GiB |
| **Total** | **821.920B** | **371.485 GB / 345.972 GiB** |

On an M3 Ultra (512 GB) the model takes about 372 GB in oMLX, leaving room for the KV cache.

## Use with mlx-lm

```bash
pip install -U "mlx-lm>=0.32.2"
mlx_lm.generate --model mlx-community/Muse-Spark-Open-816B-A42B-oQ3e \
  --prompt "Explain convolutional networks like I am 5" \
  --max-tokens 5000
```

## Use with oMLX

Download the model in [oMLX](https://github.com/jundot/omlx) and chat with it in the built-in chat UI. You can add images and set the reasoning effort from low to xhigh. Reasoning cannot be turned off, and the default (Auto) uses xhigh.

## You can also use

- [mlx-community/Muse-Spark-Open-816B-A42B-oQ4e](https://huggingface.co/mlx-community/Muse-Spark-Open-816B-A42B-oQ4e): the 4-bit oQ quant.
- [mlx-community/Muse-Spark-Open-816B-A42B-3bit](https://huggingface.co/mlx-community/Muse-Spark-Open-816B-A42B-3bit): the standard mlx-lm 3-bit quant.
- [mlx-community/Muse-Spark-Open-816B-A42B-4bit](https://huggingface.co/mlx-community/Muse-Spark-Open-816B-A42B-4bit): the standard mlx-lm 4-bit quant.

## License

Muse Model License, following the source model. See `LICENSE.md` and `USE_POLICY.md`.