---
license: apache-2.0
base_model: PowerInfer/SmallThinker-4BA0.6B-Instruct
tags:
  - mlx
  - smallthinker
  - moe
  - tool-use
  - function-calling
library_name: mlx
pipeline_tag: text-generation
---

# SmallThinker-4BA0.6B-Instruct (MLX 4-bit)

An MLX 4-bit (group size 64, affine) conversion of
[PowerInfer/SmallThinker-4BA0.6B-Instruct](https://huggingface.co/PowerInfer/SmallThinker-4BA0.6B-Instruct):
a 4B-total / roughly 0.6B-active dense-attention Mixture-of-Experts model (32 experts,
top-4, ReLU-gated), non-thinking Instruct.

## Requires an mlx_lm architecture module

Stock `mlx_lm` does not yet ship a `smallthinker` architecture, so this model will not
load with an unmodified install. Until the upstream mlx-lm PR lands, copy the included
`smallthinker.py` into your `mlx_lm/models/` directory:

```bash
cp smallthinker.py "$(python -c 'import mlx_lm,os;print(os.path.join(os.path.dirname(mlx_lm.__file__),"models"))')/"
```

Then:

```bash
python -m mlx_lm generate \
  --model Aa09876/SmallThinker-4BA0.6B-Instruct-mlx-4bit \
  --prompt "Explain a mixture-of-experts model in two sentences."
```

## Tool calling

The model uses the native Hermes tool-call format, `<tool_call>{json}</tool_call>`, and
works with servers that select a Hermes tool parser (for example rapid-mlx
`--tool-call-parser hermes`, no reasoning parser).

## Provenance and lineage

- Base weights: `PowerInfer/SmallThinker-4BA0.6B-Instruct` (Apache-2.0), pinned revision `b51db6d`
- Architecture support: a from-scratch `mlx_lm` implementation of the custom
  `SmallThinkerForCausalLM` (ReLU-gated packed-expert MoE, GQA with 12 query / 2 KV heads,
  and the model's pre-attention router-input routing). It was numerically parity-checked
  against the reference PyTorch model: BF16 greedy generation matched token-for-token,
  router top-k selection matched 100% (tie-adjusted), and per-tensor error stayed at the
  BF16 rounding floor.
- Quantization: MLX 4-bit, group size 64, affine.

## License

Apache-2.0, inherited from the base model. Attribution: PowerInfer / IPADS (SmallThinker).
This repository redistributes a quantized derivative under the same license.