---
license: mit
language:
  - en
library_name: mlx
base_model: cmu-lti/osim-4b
base_model_relation: quantized
quantized_by: liminalstoat
pipeline_tag: text-generation
tags:
  - mlx
  - apple-silicon
  - qwen3
  - human-simulation
  - user-simulation
  - behavioral-modeling
  - conversational
  - on-device
---

# OSim-4B · MLX · 4-bit

A 4-bit [MLX](https://github.com/ml-explore/mlx) build of [`cmu-lti/osim-4b`](https://huggingface.co/cmu-lti/osim-4b) — CMU's **OSim / OdysSim** human-behavior-simulation model — for running on Apple Silicon (Mac, iPhone, iPad).

This is the **instruct-derived** OSim 4B (built on `Qwen/Qwen3-4B`), so it carries the correct Qwen3 chat template and `<|im_end|>` stop token — chat works out of the box.

- **Format:** MLX · 4-bit · group size 64
- **Size:** 2.1G
- **Built with:** mlx-lm `0.31.3` on 2026-06-28

## What OSim is (read this — it is *not* an assistant)

OSim (**OdysSim**) is a family of *foundation models for human-behavior simulation* from CMU LTI. It's trained to **simulate how a person behaves in a conversation** — to play the *user*, not the helpful assistant. Prompt it like a chatbot and it will do un-assistant-like things: ask its own questions, act like someone seeking help, hold a persona. That's the model working as intended. Use it where you want a synthetic human counterpart — dialogue-system testing, user simulation, behavioral data generation.

- Base model: [`cmu-lti/osim-4b`](https://huggingface.co/cmu-lti/osim-4b) (MIT)
- Foundation: [`Qwen/Qwen3-4B`](https://huggingface.co/Qwen/Qwen3-4B) (Apache-2.0)
- Project / paper: *OdysSim — Building Foundation Models for Human Behavior Simulation* · code: [github.com/sunnweiwei/OdysSim](https://github.com/sunnweiwei/OdysSim)

## A note on quality

This is a 4-bit quant of a 4B model, so there's some loss versus full precision — expect occasional arithmetic/reasoning slips and the odd repetition. For more headroom, convert a higher-bit MLX build (5/6/8-bit) from the same source, or run [`cmu-lti/osim-4b`](https://huggingface.co/cmu-lti/osim-4b) directly on a larger machine. None of this is a prompting problem; it's the 4-bit size trade.

## Run it on Mac (Apple Silicon)

```bash
pip install mlx-lm
mlx_lm.generate --model liminalstoat/osim-4b-mlx-4bit \
  --prompt "Hi, what can you help me with?" --max-tokens 256
```

```python
from mlx_lm import load, generate
model, tokenizer = load("liminalstoat/osim-4b-mlx-4bit")
print(generate(model, tokenizer, prompt="Hi, what can you help me with?", max_tokens=256))
```

The chat template ships with the model, so `mlx_lm` applies it automatically.

## Run it on iPhone / iPad

MLX runs on-device through [mlx-swift](https://github.com/ml-explore/mlx-swift). The most direct path is Apple's [mlx-swift-examples](https://github.com/ml-explore/mlx-swift-examples) app — point it at this repo or a local copy — or your own mlx-swift harness. Some MLX-based iOS chat apps can also load custom Hugging Face MLX repos; if yours supports adding a model by ID, use `liminalstoat/osim-4b-mlx-4bit`.

## How it was made

```
source:   cmu-lti/osim-4b   (instruct-derived; Qwen3-4B foundation)
tool:     mlx_lm.convert --quantize --q-bits 4 --q-group-size 64
mlx-lm:   0.31.3
```

A straight 4-bit MLX conversion of CMU's published weights — no fine-tuning or merging, built from full-precision source (not from a pre-quantized model).

## Intended use & limitations

A research / tinkering artifact for on-device human-behavior simulation. It inherits the intended uses and limitations of the base [`cmu-lti/osim-4b`](https://huggingface.co/cmu-lti/osim-4b), plus quantization loss. Not validated for production or factual QA. Because it simulates human behavior, outputs can be inconsistent, opinionated, or persona-driven by design.

## License & attribution

- This quant: **MIT**, following the base model.
- Base: [`cmu-lti/osim-4b`](https://huggingface.co/cmu-lti/osim-4b) — MIT (CMU LTI).
- Foundation: [`Qwen/Qwen3-4B`](https://huggingface.co/Qwen/Qwen3-4B) — Apache-2.0 (Qwen Team).

## Citation

- **OdysSim** — *Building Foundation Models for Human Behavior Simulation* (CMU LTI). Code: [github.com/sunnweiwei/OdysSim](https://github.com/sunnweiwei/OdysSim).
- **Qwen3** — Qwen Team, *Qwen3 Technical Report*, arXiv:2505.09388.