Osaurus-AppleScript-8B-JANG_6M
A fast, small tool-calling model for macOS AppleScript & agentic computer-use. Given a run_applescript
tool, it emits a structured tool call with valid AppleScript to drive macOS — app automation
(Safari, Finder, Mail, Notes, Calendar, System Events), system control, clipboard, screenshots, and
do shell script — ready to execute in an agent loop. Without a tools spec, it writes AppleScript
directly (hybrid).
Built by Osaurus. Base: Zyphra/ZAYA1-8B (MoE). Quantized with JANG (6-bit affine, MLX-native) for fast on-device inference via MLX. Verified in the Osaurus runtime.
| Parameters | 8.84 B (MoE, 16 experts) |
| Quant | JANG 6-bit — 6-bit affine weights + 8-bit embeddings (MLX mx.quantize, group 32) |
| Size | ~7.4 GB |
| Tool-calling | native (<zyphra_tool_call>), run_applescript |
| Runtime | MLX (Apple Silicon) / Osaurus |
Benchmark — base vs final (held-out executable AppleScript bench, 87 tasks)
Tool-call emission = emits a run_applescript call. Compile = the emitted script is valid
AppleScript. Exec = it runs and returns the correct result (scored on the pure-computational subset
with a deterministic answer).
| Tool-call emission | Compile | Exec | |
|---|---|---|---|
| Base (Zyphra/ZAYA1-8B) | ✗ (writes raw text, no tool calls) | 28.9% | 30.0% |
| Osaurus-AppleScript-8B-JANG_6M | 100% ⭐ | 80% ⭐ | 75% ⭐ |
The fine-tune teaches structured tool-calling and valid AppleScript (base does neither). Typical app-automation tool-calls sit at the compile tier; the exec column is the hardest computational subset (string/number algorithms, shell, coercions).
Usage (MLX, tool-calling)
from mlx_lm import load, generate
model, tok = load("OsaurusAI/Osaurus-AppleScript-8B-JANG_6M")
tools = [{"type":"function","function":{"name":"run_applescript",
"description":"Execute AppleScript on macOS and return its output.",
"parameters":{"type":"object","properties":{"script":{"type":"string"}},"required":["script"]}}}]
msgs = [{"role":"user","content":"Get the URL of the front Safari tab."}]
prompt = tok.apply_chat_template(msgs, tools=tools, add_generation_prompt=True, tokenize=False)
print(generate(model, tok, prompt=prompt, max_tokens=300))
# -> <zyphra_tool_call><function=run_applescript><parameter=script> ... </parameter>...
Your agent parses the run_applescript tool call, runs the script (e.g. via osascript), and feeds
the result back. (Omit tools= to get raw AppleScript instead.)
Tiers
For higher accuracy use OsaurusAI/Osaurus-AppleScript-16B-A4B-JANG_4M. This 8B is the fast/small
tier for low-latency on-device automation.
License
Inherits the Zyphra/ZAYA1-8B license — review and comply with the base model's terms.
Made by Osaurus · contact eric@osaurus.ai