GrootTeam/Groot-19B-A3B-261023
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.
Groot is a family of open-weight reasoning models for complex real-world tasks. Mixture-of-experts, 19B total, 3B active (128 experts, 8 per token). Context: 256K tokens (config). License: apache-2.0. Vendor-reported: "Groot-19B-A3B-261023 beats both Qwen3.6-35B-A3B and Gemma-4-26B-A4B on 12 of the 16 benchmarks, for example Terminal Bench 2.1 (52.10 vs 43.82 / 26.52), NL2Repo-Bench (35.65 vs 28.77 / 16.55) and LongBench v2 (62.03 vs 48.12 / 47.99)."
- Vendor-reported: Groot-19B-A3B-261023 beats both Qwen3.6-35B-A3B and Gemma-4-26B-A4B on 12 of the 16 benchmarks, for example Terminal Bench 2.1 (52.10 vs 43.82 / 26.52), NL2Repo-Bench (35.65 vs 28.77 / 16.55) and LongBench v2 (62.03 vs 48.12 / 47.99).
- Org
- GrootTeam
- Released
- 2026-10-23
- Status
- just landed · new, unvetted
- License
- apache-2.0 (permissive)
- Parameters
- 19.4B total, 3.0B active
- Architecture
- MoE · 128 experts, 8/token · Qwen3_5MoeForConditionalGeneration
- Context
- 262,144 tokens
- Task
- image-text-to-text · vision
- Signal
- 10 HF likes · 51 downloads
Runs on
real quant files; need = weights + FP16 KV cache for 8K tokens + 1GB. A sizing calculation, not tested.
- Q4 ~13.4 GB: 16GB GPU (5060 Ti / 4060 Ti / 4080 / 5080), 16GB GPU (7800 XT / 9070 XT), Mac 24GB
- Q8 ~21.9 GB: 24GB GPU (3090 / 4090), 32GB GPU (5090), 24GB GPU (7900 XTX), Arc B60 24GB, Arc B70 32GB, Mac 36GB, Mac 48GB, CPU only, 32GB RAM (slow)
- FP16 ~39.7 GB: 48GB GPU (RTX 6000 Ada / A6000), 96GB GPU (RTX Pro 6000 Blackwell), 1× DGX Spark (128GB), 2× DGX Spark (256GB), Strix Halo 128GB unified (~96GB usable), Mac 64GB (M1 Max), Mac 96GB, Mac 128GB, Mac 192GB, Mac 256GB, Mac 512GB, CPU only, 64GB RAM (slow), CPU only, 128GB RAM (slow), CPU only, 256GB RAM (slow)
Links
First published here 2026-10-23 · updated 2026-10-23 · markdown · JSON