saorsa-1.1-tiny
saorsa-1.1-tiny is Saorsa Labs' low-memory local assistant model for Fae.
- Base model:
mlx-community/Qwen3.5-2B-4bit
- Post-training method: ORPO on Fae's assistant, tool-judgment, and memory-preference data
- Intended tier:
8–15 GB Macs
- Intended role: compact local operator with stronger tool use and assistant fit than the base 2B model
Why this model exists
Fae's low-RAM lane needs better tool calling and assistant behavior than a stock compact model can reliably provide. The current saorsa-1.1-tiny retrain improves the base 2B model where the low-memory lane was weakest: tool choice and assistant-fit behavior.
Benchmark delta vs base Qwen3.5-2B
Targeted benchmark gate:
- Tool calling:
9/10 -> 10/10
- Fae capability:
9/20 -> 9/20
- Assistant fit:
7/20 -> 9/20
- Serialization:
9/9 -> 9/9
/no_think compliance: 5/5 -> 5/5
Artifacts in the Fae repo:
- Base benchmark:
scripts/benchmark-results/qwen3.5-2b_targeted_20260314-current.json
- Fine-tuned benchmark:
scripts/benchmark-results/qwen35-2b-orpo16fullmlp-exact_targeted_20260314-2004.json
Usage
This model is intended to replace the standard 2B auto-selected lane in Fae while leaving the 4B, 9B, and 27B lanes unchanged.
Notes
- This is a Qwen-compatible MLX model and is intended for local Apple Silicon inference.
- Training data and extraction scripts live in the Fae repository.
- The model is designed for assistant behavior, tool choice, and memory judgment, not generic leaderboard optimization.
