---
license: apache-2.0
base_model: stepfun-ai/Step-3.7-Flash
base_model_relation: quantized
library_name: mlx
pipeline_tag: image-text-to-text
tags:
  - mlx
  - omlx
  - oq
  - oq5
  - quantized
  - step3p7
  - vision-language
  - multimodal
  - moe
  - safetensors
---

# Step-3.7-Flash-oQ5-MLX

This repository contains an oMLX `oQ5` mixed-precision MLX quantization of
[`stepfun-ai/Step-3.7-Flash`](https://huggingface.co/stepfun-ai/Step-3.7-Flash).

Step-3.7-Flash is a sparse Mixture-of-Experts vision-language model from
StepFun. The upstream model card describes it as a 198B-parameter model with a
196B language backbone, a 1.8B vision encoder, approximately 11B active
parameters per token, and a 256K context window.

## Quantization

| Field | Value |
| --- | --- |
| Method | oMLX oQ mixed-precision MLX |
| Quantization | oQ5 |
| Base model revision | `5f6244077ac62e04eec3f320501ff8c2b293373a` |
| Model type | step3p7 / step3p5 text backbone |
| Group size | 64 |
| Quantization mode | affine |
| Base bits | 5 |
| Effective plan | 5.79 bpw |
| Output shards | 27 safetensors |
| Output size | 131.0 GiB |
| Non-quantized/scales dtype | bfloat16 |
| Vision weights | preserved |
| Native MTP weights | not present in upstream weights |

## Notes

Vision weights are preserved from the upstream model.

Native MTP weights are not included in this artifact. The upstream `text_config` declares `num_nextn_predict_layers=3`, but the published safetensors index does not contain `mtp.*` weights, so oMLX keeps the quantized output self-consistent with Native MTP disabled.

This is an unofficial quantized derivative. It is not affiliated with,
sponsored by, or endorsed by StepFun.

## Validation

Artifact validation completed locally with the bundled oMLX runtime on macOS:

```text
source model: stepfun-ai/Step-3.7-Flash
source revision: 5f6244077ac62e04eec3f320501ff8c2b293373a
quantization: oQ5
config.json: present
model.safetensors.index.json: present
safetensor shards: 27
vision tensors: present
mtp tensors: not present
```

Generation smoke testing is intentionally not claimed here because Step-3.7-Flash
is a very large VLM/MoE checkpoint and runtime support depends on the local
MLX/oMLX build and available unified memory.

## Usage

Use an MLX/oMLX build that supports the packaged Step3p7 architecture and
multimodal processor.

```bash
huggingface-cli download \
  --local-dir Step-3.7-Flash-oQ5-MLX \
  dawncr0w/Step-3.7-Flash-oQ5-MLX
```

For a text-only smoke test, adapt the command to your local MLX/oMLX runtime:

```bash
python -m mlx_lm generate \
  --model /path/to/Step-3.7-Flash-oQ5-MLX \
  --prompt "Hello" \
  --max-tokens 32 \
  --temp 0
```

For multimodal inference, use an oMLX/MLX-VLM build that supports Step3p7
`image-text-to-text` models and pass the model directory as the local checkpoint.

## License And Notice

The base model is distributed under the Apache License 2.0. This quantized
artifact follows the same license.