nvidia/Flora-Rewarder
main boardmodel
Training labels are a combination of human-written annotations, automatic success signals recorded with the data, and VLM-generated annotations. Dense, 28B params. Context: 256K tokens (config). License: nvidia-license.
- Org
- nvidia
- Released
- 2026-10-02
- Status
- main board
- License
- nvidia-license (restricted)
- Parameters
- 27.8B
- Architecture
- dense · Qwen3_5ForConditionalGeneration
- Context
- 262,144 tokens
- Task
- video-text-to-text · vision
- Signal
- 17 HF likes · 1024 downloads
Runs on
estimate from params; need = weights + FP16 KV cache for 8K tokens + 1GB. A sizing calculation, not tested.
- Q4 ~19.8 GB (estimated size): 24GB GPU (3090 / 4090), 32GB GPU (5090), 24GB GPU (7900 XTX), Mac 36GB, CPU only, 32GB RAM (slow)
- Q8 ~32.6 GB (estimated size): 48GB GPU (RTX 6000 Ada / A6000), Mac 48GB, Mac 64GB (M1 Max), CPU only, 64GB RAM (slow)
- FP16 ~58.7 GB (estimated size): 96GB GPU (RTX Pro 6000 Blackwell), 1× DGX Spark (128GB), 2× DGX Spark (256GB), Strix Halo 128GB unified (~96GB usable), Mac 96GB, Mac 128GB, Mac 192GB, Mac 256GB, Mac 512GB, CPU only, 128GB RAM (slow), CPU only, 256GB RAM (slow)
Links
First published here 2026-10-02 · updated 2026-10-20 · markdown · JSON