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Open-weight model · Robotics

GR00T-N1.7-ForceBenchmark-MoE-vasev6-MLP-30K-20260926

by Linqi Han HanLinqi/GR00T-N1.7-ForceBenchmark-MoE-vasev6-MLP-30K-20260926

GR00T-N1.7-ForceBenchmark-MoE-vasev6-MLP-30K-20260926 is an open-weight model for robotics from Linqi Han. It has 3.2B parameters. At 16-bit it needs about 7.6 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.

This repository contains the model-only checkpoint saved at 30,000 training steps. The files at the repository root are the original contents of checkpoint-30000. Full model and processor settings are in config.json, processorconfig.json, and experimentcfg/.

Parameters3.2B
Context—
Weights7.0 GB
License—
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve GR00T-N1.7-ForceBenchmark-MoE-vasev6-MLP-30K-20260926 (3.2B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso fits
16-bit 6.3 GB 7.6 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 3.2 GB 3.8 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 1.6 GB 1.9 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Oct 18, 2026.

GR00T-N1.7-ForceBenchmark-MoE-vasev6-MLP-30K-20260926 on every accelerator the SAVRN Index prices, at every precision

Model Card

This repository contains the model-only checkpoint saved at 30,000 training steps. The files at the repository root are the original contents of checkpoint-30000. Full model and processor settings are in config.json, processorconfig.json, and experimentcfg/. The training run did not include an evaluation. Source checkpoint: outputs/moeobs2h10fourtasks20260926191812/pair67/vasev6/moe/checkpoint-30000.

Excerpt from the card by Linqi Han.

Configuration

Architecture
Gr00tN1d7
Hidden size
1,024
Model type
Gr00tN1d7

Identity and Version

Repository
HanLinqi/GR00T-N1.7-ForceBenchmark-MoE-vasev6-MLP-30K-20260926
Publisher
Linqi Han
Task
Robotics
Modality
Control
Library
Not stated by the source
Parameters
3.2B parameters
Languages
moe
Revision
e2ab4f0b107b0dfe3e1b467e05ec04002f6ec356
First published
2026-09-27
Last updated
2026-09-27

Files and Weights

17 files, 7.0 GB in total. The weights are 3 files totalling 7.0 GB in bin, safetensors.

Weights3 files · 7.0 GB
Configuration12 files · 651.2 KB
Documentation1 file · 927 B
Repository1 file · 1.5 KB
Every file
FileTypeSizeSHA-256
model-00001-of-00002.safetensorsWeights5.0 GB f3ff92b5699c
model-00002-of-00002.safetensorsWeights2.0 GB 066b8e2299a6
training_args.binWeights8.0 KB a46b3902384a
config.jsonConfiguration2.9 KB —
embodiment_id.jsonConfiguration2.2 KB —
experiment_cfg/conf.yamlConfiguration6.0 KB —
experiment_cfg/config.yamlConfiguration5.9 KB —
experiment_cfg/dataset_statistics.jsonConfiguration6.6 KB —
experiment_cfg/final_model_config.jsonConfiguration2.2 KB —
experiment_cfg/final_processor_config.jsonConfiguration12.5 KB —
model.safetensors.index.jsonConfiguration182.9 KB —
processor_config.jsonConfiguration3.1 KB —
statistics.jsonConfiguration6.6 KB —
trainer_state.jsonConfiguration420.1 KB —
wandb_config.jsonConfiguration51 B —
README.mdDocumentation927 B —
.gitattributesRepository1.5 KB —

License and Download

License
Not stated by the source
Access
Open weights, no gate
Download size
7.0 GB
Download from Linqi Han

Released by Linqi Han through its official repository on Hugging Face.

Built From

Memory Requirements

PrecisionWeights in memory
As published7.0 GB
16-bit6.3 GB
8-bit3.2 GB
4-bit1.6 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About GR00T-N1.7-ForceBenchmark-MoE-vasev6-MLP-30K-20260926

How much GPU memory does GR00T-N1.7-ForceBenchmark-MoE-vasev6-MLP-30K-20260926 need?

About 7.6 GB at 16-bit and 1.9 GB at 4-bit: the weights (3.2B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run GR00T-N1.7-ForceBenchmark-MoE-vasev6-MLP-30K-20260926 on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

Similar Models

This repository contains the model-only checkpoint saved at 30,000 training steps. The files at the repository root are the original contents of checkpoint-30000. Full model and processor settings are in config.json, processorconfig.json, and experimentcfg/. The training run did not include an evaluation. Source checkpoint: outputs/moeobs2h10fourtasks20260926191812/pair67/usb/moe/checkpoint-30000.

Open weights 3.2B parameters

This repository contains the model-only checkpoint saved at 30,000 training steps. The files at the repository root are the original contents of checkpoint-30000. Full model and processor settings are in config.json, processorconfig.json, and experimentcfg/. The training run did not include an evaluation. Source checkpoint: outputs/moeobs2h10fourtasks20260926191812/pair45/whiteboardv9/moe/checkpoint-30000.

Open weights 3.2B parameters

This repository contains the model-only checkpoint saved at 30,000 training steps. The files at the repository root are the original contents of checkpoint-30000. Full model and processor settings are in config.json, processorconfig.json, and experimentcfg/. The training run did not include an evaluation. Source checkpoint: outputs/moeobs2h10fourtasks20260926191812/pair45/weightsorting/moe/checkpoint-30000.

Open weights 3.2B parameters

This repository contains the model-only checkpoint saved at 30,000 training steps. The files at the repository root are the original contents of checkpoint-30000. Full model and processor settings are in config.json, processorconfig.json, and experimentcfg/. The training run did not include an evaluation. Source checkpoint: outputs/moeforcetransformertuningobs2h1020260926223332/usbk6s1e4f384xformer/usb/moe/checkpoint-30000.

Open weights 3.2B parameters

This repository contains the model-only checkpoint saved at 30,000 training steps. The files at the repository root are the original contents of checkpoint-30000. Full model and processor settings are in config.json, processorconfig.json, and experimentcfg/. The training run did not include an evaluation. Source checkpoint: outputs/moeforcetransformertuningobs2h1020260926223332/whiteboardv9k8s1e6f384xformer/whiteboardv9/moe/checkpoint-30000.

Open weights 3.2B parameters

This repository contains the model-only checkpoint saved at 30,000 training steps. The files at the repository root are the original contents of checkpoint-30000. Full model and processor settings are in config.json, processorconfig.json, and experimentcfg/. The training run did not include an evaluation. Source checkpoint: outputs/moeforcetransformertuningobs2h1020260926223332/vasev6k12s1e6f384xformer/vasev6/moe/checkpoint-30000.

Open weights 3.2B parameters