gevaertlab/MANTA-27B
just landed · new, unvettedmodel
New, unvetted: created or first seen in the last few days, not from a trusted org and not past the signal threshold yet.
MANTA (Medical Answers, Natively from Text And images) is a medical decision model developed by the Gevaert Lab at the Department of Computational Medicine, Stanford University. Dense, 27B params. Context: 256K tokens (config). License: apache-2.0.
- Org
- gevaertlab
- Released
- 2026-11-10
- Status
- just landed · new, unvetted
- License
- apache-2.0 (permissive)
- Parameters
- 27.5B
- Architecture
- dense · MantaForDecision
- Context
- 262,144 tokens (config.json)
- Task
- text-classification · text
- Signal
- 13 HF likes · 156 downloads
Runs on
mixed: real files + estimate; need = weights + FP16 KV cache for 8K tokens + 1GB. A sizing calculation, not tested.
- Q4 ~19.6 GB (estimated size): 24GB GPU (3090 / 4090), 32GB GPU (5090), 24GB GPU (7900 XTX), Mac 36GB, CPU only, 32GB RAM (slow)
- Q8 ~32.3 GB (estimated size): 48GB GPU (RTX 6000 Ada / A6000), Mac 48GB, Mac 64GB (M1 Max), CPU only, 64GB RAM (slow)
- FP16 ~58.1 GB: 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 2026-11-10 · updated 2026-11-14 · markdown · JSON