g05

G0.5 VLA, RoboDojo’s own checkpoint (joint actions, both arms), through XPolicyLab’s G05 adapter

• Kind: policy
• Protocol: xpolicylab
• Default port: 19005
• VRAM: 16.4 GB
• Load time: about 120 s
• Skills that use a policy: vla
• Configurations that name it: –

What the model is told

A visuomotor policy trained on whole RoboDojo tasks: each demonstration starts at the start pose and finishes the task, labelled with the task’s own instruction; it moves both arms (joint actions) with skilled contact, many times a second. It does best in exactly that setting: from the untouched start pose, with the task’s own instruction, left to run. It does not reason: it cannot read words, numbers or pictures to decide what goes where, does not remember what it saw earlier, and does not notice its own mistakes. Reliable (it usually finishes by itself): putting a few separate objects into a bin, case or box. Partial (it often does part and leaves the rest): stacking blocks in a pile or tower; folding cloth; pouring a liquid or small loose objects into a container; nesting bowls or cups; tidying objects onto their places; filling a holder with several items; putting an item into an appliance; packing several objects into a box; standing tubes upright in a rack or driving a screw (rarely all the way). Unreliable (it rarely helps): hanging items on a hook or rack; sorting objects into groups; filling a tray of small slots; building a shape from parts; pushing or sweeping objects to an exact pose; any task where what goes where depends on reading words, numbers, an equation, a picture or a demonstration; remembering what happened earlier (hidden, swapped or shown objects, buttons in order); catching objects on a moving conveyor; small precise insertions (a key, coin or plug); ordering by size; playing notes or stacking a toy in a given order. Signs it is failing: the arms stop moving while objects are not where the task needs them; the same reach is repeated; an object is knocked over or off the table; the jaws close fully on nothing after carrying something.

Weights

harness fetch g05 --deploy <machine>

Directory	Source	From
<weights>/g05	modelscope_dataset	RoboDojo-Benchmark/RoboDojo (ckpt/RoboDojo/G05/RoboDojo-sim-arx_x5-joint-0)
<weights>/g05-processor	modelscope_model	Qwen/Qwen3.5-2B-Base

Notes

The checkpoint config points at a processor path that is not shipped; OpenGalaxea/G05 on Hugging Face is gated, and its qwen3_5_2b_base_processor files match Qwen/Qwen3.5-2B-Base (ModelScope) byte for byte. The description (what the model is told) names kinds of manipulation, never tasks: it generalises G0.5’s own scores run alone through run_policy on development layouts (configs/experiments/policy-alone-dev.toml; scripts/policy_card.py sorts them), 2026-10-13: 2 layouts of each task, 4 for the five tasks whose kind moved from the earlier description (derived from official evaluation pack 0); 2 reliable, 12 partial, 24 unreliable. Not measured: cover_blocks, swap_blocks and play_tic_tac_toe (every arrangement is an evaluation layout, so none is left for development) and imitate_sorting_sequence (RoboDojo marks both layouts unstable mid-episode).

Manifest

kind = "policy"
summary = "G0.5 VLA, RoboDojo's own checkpoint (joint actions, both arms), through XPolicyLab's G05 adapter"
protocol = "xpolicylab"
port = 19005
# Measured on a 3090: 16.4 GB. The first request after a start takes 15-50 s.
vram_gb = 16.4
load_seconds = 120
needs_files = ["{weights}/g05/checkpoints/checkpoint", "{weights}/g05-processor/tokenizer.json",
               "{xpolicylab}/policy/G05/G05"]
notes = """The checkpoint config points at a processor path that is not shipped; OpenGalaxea/G05 on Hugging Face \
is gated, and its qwen3_5_2b_base_processor files match Qwen/Qwen3.5-2B-Base (ModelScope) byte for byte. \
The description (what the model is told) names kinds of manipulation, never tasks: it generalises G0.5's \
own scores run alone through run_policy on development layouts (configs/experiments/policy-alone-dev.toml; \
scripts/policy_card.py sorts them), 2026-10-13: 2 layouts of each task, 4 for the five tasks whose kind moved \
from the earlier description (derived from official evaluation pack 0); 2 reliable, 12 partial, 24 unreliable. \
Not measured: cover_blocks, swap_blocks and play_tic_tac_toe (every arrangement is an evaluation layout, so \
none is left for development) and imitate_sorting_sequence (RoboDojo marks both layouts unstable mid-episode)."""

[client]
url = "{url}"
description = """A visuomotor policy trained on whole RoboDojo tasks: each demonstration starts at the start \
pose and finishes the task, labelled with the task's own instruction; it moves both arms (joint actions) with \
skilled contact, many times a second. It does best in exactly that setting: from the untouched start pose, with \
the task's own instruction, left to run. It does not reason: it cannot read words, numbers or pictures to decide \
what goes where, does not remember what it saw earlier, and does not notice its own mistakes. \
Reliable (it usually finishes by itself): putting a few separate objects into a bin, case or box. \
Partial (it often does part and leaves the rest): stacking blocks in a pile or tower; folding cloth; pouring a \
liquid or small loose objects into a container; nesting bowls or cups; tidying objects onto their places; \
filling a holder with several items; putting an item into an appliance; packing several objects into a box; \
standing tubes upright in a rack or driving a screw (rarely all the way). \
Unreliable (it rarely helps): hanging items on a hook or rack; sorting objects into groups; filling a tray of \
small slots; building a shape from parts; pushing or sweeping objects to an exact pose; any task where what \
goes where depends on reading words, numbers, an equation, a picture or a demonstration; remembering what \
happened earlier (hidden, swapped or shown objects, buttons in order); catching objects on a moving conveyor; \
small precise insertions (a key, coin or plug); ordering by size; playing notes or stacking a toy in a given \
order. \
Signs it is failing: the arms stop moving while objects are not where the task needs them; the same reach is \
repeated; an object is knocked over or off the table; the jaws close fully on nothing after carrying something."""

[xpolicylab]
policy = "G05"
ckpt_name = "RoboDojo-sim-arx_x5-joint-0"
action_type = "joint"
cwd = "{xpolicylab}/policy/G05/G05"
pythonpath = ["{xpolicylab}/policy/G05/G05/src", "{xpolicylab}/policy/G05/G05", "{robodojo}", "{xpolicylab}"]

[xpolicylab.overrides]
ckpt_path = "{weights}/g05/checkpoints/checkpoint"
g05_root = "{xpolicylab}/policy/G05/G05"
action_source = "fm"
hydra_overrides = "['model.model_arch.hf_processor_path={weights}/g05-processor','model.processor.tokenizer_params.pretrained_model_name_or_path={weights}/g05-processor']"

[[weights]]
dir = "g05"
modelscope_dataset = "RoboDojo-Benchmark/RoboDojo"
root = "ckpt/RoboDojo/G05/RoboDojo-sim-arx_x5-joint-0"

[[weights]]
dir = "g05-processor"
modelscope_model = "Qwen/Qwen3.5-2B-Base"
exclude = ["*.safetensors", "*.bin", "*.pt"]