ARC-AGI-3 Toolkit — models, repos, datasets, plan
Collection
Best open models for ARC-AGI-3, 45 mirrored harness repos, all public trace datasets, and the plan to top-3. • 17 items • Updated
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
id: string
id_no: int64
title: string
code_file: string
language: string
kernel_type: string
is_private: bool
enable_gpu: bool
enable_tpu: bool
enable_internet: bool
keywords: list<item: string>
child 0, item: string
dataset_sources: list<item: string>
child 0, item: string
kernel_sources: list<item: null>
child 0, item: null
competition_sources: list<item: string>
child 0, item: string
model_sources: list<item: null>
child 0, item: null
docker_image: string
machine_shape: string
to
{'id': Value('string'), 'title': Value('string'), 'code_file': Value('string'), 'language': Value('string'), 'kernel_type': Value('string'), 'is_private': Value('bool'), 'enable_gpu': Value('bool'), 'enable_tpu': Value('bool'), 'enable_internet': Value('bool'), 'keywords': List(Value('string')), 'dataset_sources': List(Value('string')), 'kernel_sources': List(Value('null')), 'competition_sources': List(Value('string')), 'model_sources': List(Value('null')), 'docker_image': Value('string'), 'machine_shape': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
id: string
id_no: int64
title: string
code_file: string
language: string
kernel_type: string
is_private: bool
enable_gpu: bool
enable_tpu: bool
enable_internet: bool
keywords: list<item: string>
child 0, item: string
dataset_sources: list<item: string>
child 0, item: string
kernel_sources: list<item: null>
child 0, item: null
competition_sources: list<item: string>
child 0, item: string
model_sources: list<item: null>
child 0, item: null
docker_image: string
machine_shape: string
to
{'id': Value('string'), 'title': Value('string'), 'code_file': Value('string'), 'language': Value('string'), 'kernel_type': Value('string'), 'is_private': Value('bool'), 'enable_gpu': Value('bool'), 'enable_tpu': Value('bool'), 'enable_internet': Value('bool'), 'keywords': List(Value('string')), 'dataset_sources': List(Value('string')), 'kernel_sources': List(Value('null')), 'competition_sources': List(Value('string')), 'model_sources': List(Value('null')), 'docker_image': Value('string'), 'machine_shape': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
ARC-AGI-3 GitHub Collection — every useful repo, mirrored & organized
Mirrored 2026-09-29 · 45 repositories covering the full public ARC-AGI-3 landscape, discovered via GitHub API search (6 query buckets, 152 unique hits → 45 selected for direct competition relevance).
Companion Space: Nabidnur/arc-agi-3-command-center · Models index: Nabidnur/arc-agi-3-models-and-analysis · Datasets: Nabidnur/arc-agi-3-datasets-combined
Layout
repos/<owner>__<name>/— full source of each repo (.gitstripped, exact snapshot 2026-09-29)repos/GITHUB-INDEX.md— annotated index: what each repo is, why it matters, star countprovenance/github_discovery_ranked.json— raw ranked discovery dump (152 repos with stars/topics/queries)
The crown jewels
| Path | Why |
|---|---|
repos/Tufalabs__duck-harness |
Milestone-1 winner (our base harness) + full example-run trace corpus (events.jsonl + transcripts + prompts for all 25 games × levels) |
repos/ryanbbrown__Retrodict |
183/183, 99.86% RHAE, $654 — log-as-context + plan-queue verification + playbook memory |
repos/NIMI-research__Tycho |
183/183, 100.00 RHAE — deterministic Moore-machine rendering |
repos/synchopate__arc-agi-crystalline |
180/183 — source-reading + ACT-R cognitive memory |
repos/Alexyskoutnev__TWIN-ARC-AGI-3 |
179/183 — executable game twin, plan-in-twin, ExecuteChecked |
repos/alexisfox7__PRO-LONG |
+18pp, 4.2–5.8× token reduction — append-only searchable log |
repos/studio-dots-ai__TELL |
43.9% single-conversation experiential learning |
repos/NVIDIA__dream-team |
NVIDIA's multi-agent ARC-AGI-3 solver (AVO lineage) |
repos/feng-rrRay__Continual-Harness-ARC-AGI-3 |
Continual skill library across games |
repos/arcprize__* |
Official: ARC-AGI-3-Agents, Kaggle-Starter, benchmarking, ARC-AGI-1/2 data, community leaderboard |
repos/Hisernberg__checkmpobbyacckraggle |
Complete Kaggle research archive: 237-submission history, leaderboard snapshots, kernel index |
Licenses
Each mirrored repo keeps its original LICENSE file. All content © original authors — mirrored for research access with attribution; see per-repo provenance in repos/GITHUB-INDEX.md.
Milestone-2 Update (2026-10-02)
ARC-AGI-3 Milestone 2 = leaderboard snapshot at Sept 30, 2026 23:59 UTC (open-source notebooks). Podium: dfranzen 27.89 · lordhansolo 23.84 · sirikilohit/rellik13 22.53 · richardcsaky 20.00. All four run the same lineage: Tufa Duck/TAAF harness + Qwen3.8-Flash-Next (Intel W4A16 AutoRound or mixed NVFP4/FP8) + MTP speculative decoding + FP8 E4M3 KV cache (1.0–1.4M-token pools) + 45–57k rolling history with blockwise hysteresis trims + score-aware scheduling.
The one ablation that matters: FP8 KV + longer history alone took rellik13 14.49 → 22.53 with zero prompt changes; KV pool was 91–97% full — memory, not decode TPS, was the bottleneck.
Full deconstruction incl. the 4→27 thought process, per-notebook serving configs, LB scoring factors
(level = min(115, (baseline/your_actions)²×100)), top-notebook gap analysis, and the 30–40+ fusion plan:
see docs/27-milestone2-analysis.md in arc-agi-3-models-and-analysis and this repo's milestone2/ folder.
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