Updated 4 h ago · first seen 11 Sept 2026
model_01M294Z7R89B5M09KM5RAJ2VQ9
Overview
Identity
- Canonical model
- Yesidentity confidence: highOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
- Official checkpoints
- official_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
- Artifacts
- 1 quantization0 official · 1 third-partySeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
- Provider deployments
- None recorded
- API aliases
- NoneIdentifiers under which providers and evaluators refer to this model.
- Folded evaluation variants
- 0Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.
Openness
Open weights— weights downloadable under Other; 7 dimensions unknown.
Weights downloadable under a permissive or Creative Commons licence allowing commercial use; code or data may be missing.
Weights
Yes
Inference code
—
Training code
—
Training data
—
Dataset
—
Commercial use
—
Redistribution
—
Derivatives
—
Licence: Other (unclassified licence) (unknown · stated as “other”)
dimensions marked null are unknown, not false
Key facts
- Release date
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- Model card
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
Architecture
- Parameters
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- Weights dtype
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- File size
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- Library name
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- Pipeline tag
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
- Hugging Face repo
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 5 d agomedium
Capabilities
Modalities
- Modalities
- imagetextvideo
- Input
- imagetext
- Output
- video
Capabilities
Tool calling
Unavailable
Structured output
Unavailable
Reasoning
Unavailable
Vision
Unavailable
Audio
Unavailable
Fine-tuning available
Unavailable
No capability flags have been observed from a source yet — we do not infer them.
No structured attributes yet.
Hardware fit37
Assumptions (7)
- Estimated, not measured: weights = parameters × bytes/param × 1.15 runtime overhead (or the observed artifact file size when one is recorded).
- bytes/param: 4bit = 0.5, 8bit = 1.0, fp16 = 2.0 (uniform quantization, no per-layer exceptions).
- KV cache: 2 × layers × kv_heads × head_dim × 2 bytes × context × batch when the architecture is known; otherwise 0.5 GB per 8 192 tokens (× batch), independent of architecture (GQA/MLA models need less).
- A model 'fits' when the estimate is at most the device memory minus 2 GB reserved for the OS and framework.
- Mixture-of-experts models are estimated on total parameters (all experts must be resident); active parameters are ignored.
- Device memory uses the largest configuration when several are listed (e.g. Apple silicon tiers).
- Multi-GPU: device memories are summed; interconnect bandwidth, tensor-parallel replication and pipeline bubbles are not modelled.
Lineage
Open in Graph →Versions & Artifacts1
Version history
Licensefirst observation only
11 Sept 2026current
Opennessfirst observation only
11 Sept 2026current
Parametersfirst observation only
11 Sept 2026current
Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.
Artifacts 1
quantization 1
- unsloth/MiniMax-H3-GGUFUnsloth · GGUF—
Change history76
Viewing AI Atlas as of 15 Sept 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.
Back to today →Attributes as of 15 Sept 2026 26 claims in force
- Release date
- 28 Jul 2026
- Openness
- open-weights
- License
- Other
- Parameters
- 33.1B
- Modalities
- image, text, video
- Input modalities
- image, text
- Output modalities
- video
- File size
- 66.3 GB
- Hugging Face repo
- MiniMaxAI/MiniMax-H3
- Pipeline tag
- image-text-to-video
- Model card
- Downloads
- 4,906,989
- Likes
- 5,329
- Access
- open
- Gated
- No
- Hf inference providers
- fal-ai, wavespeed
- Last modified
- 2026-08-13T01:46:29+00:00
- Library name
- minimax-h3
- License key
- Other
- License name
- minimax-h3-community-license-agreement
- License raw
- other
- License url
- LICENSE
- Downloads all time
- 7,301,064
- Tags
- minimax-h3, diffusers, safetensors, text-to-video, image-to-video, image-text-to-video, video-to-video, text-to-audio-video, image-to-audio-video, image-text-to-audio-video, video-to-audio-video, audio-to-audio-video, audio-video-generation, multimodal, synchronized-audio-video, reference-to-audio-video
- Weights available
- Yes
- Weights dtype
- BF16, F32
Release daterelease_date1
Opennessopenness1
Licenselicense1
Parametersparameter_count1
Modalitiesmodalities1
Input modalitiesmodalities_input1
Output modalitiesmodalities_output1
File sizefile_size_gb1
Hugging Face repohf_repo1
Pipeline tagpipeline_tag1
Model cardmodel_card_url1
Downloadsmetric.downloads6
Likesmetric.likes41
Accessaccess1
Gatedgated1
Hf inference providershf_inference_providers1
Last modifiedlast_modified1
Library namelibrary_name1
License keylicense_key1
License namelicense_name1
License rawlicense_raw1
License urllicense_url1
Downloads all timemetric.downloads_all_time6
Weights availableweights_available1
Weights dtypeweights_dtype1
Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →
Provenance
Attributed facts
27
Source tiers
T227
Freshest observation
5 h ago
Conflicts
None
Source documents 4
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.
Data quality (56/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →