FlyMy.AI’s small decision model: a LoRA adapter and pointer head on Qwen3-0.6B-Base, about 0.6B parameters in total. It returns native probabilities for Choice, Score and Noul questions. Like Decision 2B it is an evaluation preview whose weights are not cleared for commercial use.
A workable 0.61B-parameter dense decision model from FlyMy.AI. Treat the modality benchmarks above as the leading indicator of fit — composite scoring across modalities is still maturing.
Generated from this model’s benchmarks and ranking signals. Editor reviews refine it over time.
Access model weights, configuration files, and documentation.
Benchmark data sourced from: Hugging Face, Arena.ai, Artificial Analysis.
The top devices for this model at 4-bit, ranked by fit and speed.
| Device | Grade | VRAM |
|---|---|---|
| ACEMAGIC M1A Pro (i9-13900HK + ARC A770)ACEMAGIC | SS | 0.9 GB |
| Acer Veriton GN100 AI MiniAcer | SS | 0.9 GB |
| AI TOP ATOM ATAGB10-9003Gigabyte | SS | 0.9 GB |
| AMD Instinct MI300XAMD | SS | 0.9 GB |
| AMD Instinct MI325XAMD | SS | 0.9 GB |

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NVIDIA GeForce RTX 3060Vast.ai · Spot · 12 GB VRAM | $0.04 |
NVIDIA GeForce RTX 3060Vast.ai · On-Demand · 12 GB VRAM | $0.04 |
NVIDIA GeForce RTX 3080 TiVast.ai · Spot · 12 GB VRAM | $0.04 |
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NVIDIA GeForce RTX 4060 TiVast.ai · Spot · 8 GB VRAM | $0.07 |
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