Updated 33 min ago · first seen 11 Sept 2026
company_01M293SNYDKSFZQFER1GB4EXKN
- Country
- US
- T2 · 33 min ago
- Founded
- 1976
- T2 · 33 min ago
- HQ
- Cupertino, California
- T2 · 33 min ago
- Kind
- company
- T2 · 33 min ago
Specification
- Country
- US
Source:AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2observed 33 min agomedium
- Domains
- apple.com, machinelearning.apple.com
Source:AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2observed 33 min agomedium
- Founded
- 1976
Source:AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2observed 33 min agomedium
- GitHub org
- apple
Source:AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2observed 33 min agomedium
- Headquarters
- Cupertino, California
Source:AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2observed 33 min agomedium
- Hugging Face org
- apple
Source:AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2observed 33 min agomedium
- Kind
- company
Source:AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2observed 33 min agomedium
- Website
Source:AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2observed 33 min agomedium
Each value shows its source, tier and observation time. Conflicting claims are kept side by side and flagged — never averaged. How AI Atlas records facts →
Provenance
Attributed facts
8
Source tiers
T28
Freshest observation
33 min ago
Conflicts
None
Papers 10
published 11 Sept 2026authors 5arXiv 2609.03377
- Putting Captions to the Test: Evaluating Video Caption Quality through Multiple-Choice Question AnsweringAppleActive
published 11 Sept 2026authors 5arXiv 2609.09973
published 11 Sept 2026authors 5arXiv 2609.02796
published 2 Sept 2026authors 2arXiv 2609.01215
published 28 Aug 2026authors 3arXiv 2608.26133
- LLMs Are Not (Consistently) Bayesian: Quantifying Internal (In)consistencies of LLMs’ Probabilistic BeliefsAppleActive
published 28 Aug 2026authors 5arXiv 2605.06915
published 27 Aug 2026authors 5arXiv 2608.23812
published 26 Aug 2026authors 5arXiv 2608.23943
- IDEA Prune: An Integrated Enlarge-and-Prune Pipeline in Generative Language Model PretrainingAppleActive
published 26 Aug 2026authors 5arXiv 2503.05920
published 26 Aug 2026authors 3arXiv 2608.23911
Repositories 1
This repository contains the official implementation of "FastVLM: Efficient Vision Encoding for Vision Language Models" - CVPR 2025
stars 7,417
| Model | Params | Context | Openness | Released | Status | Quality |
|---|---|---|---|---|---|---|
| OpenELM-1_1B-Instruct | 1.08B | — | open-weights | — | active | |
| DFN5B-CLIP-ViT-H-14-378 | — | — | open-weights | — | active | |
| DFN2B-CLIP-ViT-B-16 | — | — | open-weights | — | active | |
| DFN5B-CLIP-ViT-H-14 | — | — | open-weights | — | active | |
| aimv2-large-patch14-224-lit | 436.7M | — | open-weights | — | active | |
| DFN2B-CLIP-ViT-L-14 | — | — | open-weights | — | active | |
| DepthPro-hf | 952M | — | open-weights | — | active | |
| MobileCLIP-S2-OpenCLIP | — | — | open-weights | — | active | |
| DFN2B-CLIP-ViT-L-14-39B | — | — | open-weights | — | active | |
| mobilevit-small | — | — | open-weights | — | active | |
| MobileCLIP-S1-OpenCLIP | — | — | open-weights | — | active | |
| FastVLM-0.5B | 758.8M | — | open-weights | — | active | |
| mobilevit-xx-small | — | — | open-weights | — | active | |
| mobilevitv2-1.0-imagenet1k-256 | — | — | open-weights | — | active | |
| coreml-mobileclip | — | — | open-weights | — | active | |
| DepthPro | — | — | open-weights | — | active | |
| OpenELM-270M | 271.5M | — | open-weights | — | active | |
| FastVLM-1.5B | 1.91B | — | open-weights | — | active | |
| Sharp | — | — | open-weights | — | active | |
| deeplabv3-mobilevit-xx-small | — | — | open-weights | — | active |
This repository contains the official implementation of "FastVLM: Efficient Vision Encoding for Vision Language Models" - CVPR 2025
stars 7,417
As of
Rewind the record: see this entity's attributes exactly as AI Atlas knew them on a given day.
Claim history
Countrycountry1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| US | → current | current | AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2 | medium | curated |
Domainsdomains1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| apple.com, machinelearning.apple.com | → current | current | AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2 | medium | curated |
Foundedfounded1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| 1976 | → current | current | AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2 | medium | curated |
GitHub orggithub_org1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| apple | → current | current | AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2 | medium | curated |
Headquartersheadquarters1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| Cupertino, California | → current | current | AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2 | medium | curated |
Hugging Face orghf_org1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| apple | → current | current | AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2 | medium | curated |
Kindorg_kind1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| company | → current | current | AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2 | medium | curated |
Websitewebsite1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| https://www.apple.com | → current | current | AI Atlas curated registry (YAML, versioned in git, every entry carries its source URL)T2 | medium | curated |
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 →
New model: deeplabv3-mobilevit-xx-small (Apple)
huggingfaceNew model: mobilevitv2-1.0-imagenet1k-256 (Apple)
huggingfaceNew model: aimv2-large-patch14-224-lit (Apple)
huggingfaceNew paper: Luce: Relightable Gaussians for 3D Asset Generation (Apple)
apple_ml- New paperPaperIDEA Prune: An Integrated Enlarge-and-Prune Pipeline in Generative Language Model PretrainingApple
New paper: IDEA Prune: An Integrated Enlarge-and-Prune Pipeline in Generative Language Model Pretraining (Apple)
apple_ml New paper: PROOF-Gen: From Optimized Data to Better Distillation (Apple)
apple_ml- New paperPaperFrom Preferences to Principles: Rubric-Based Alignment for Grounded Knowledge AnswersApple
New paper: From Preferences to Principles: Rubric-Based Alignment for Grounded Knowledge Answers (Apple)
apple_ml New paper: Agent Seer: Synthesizing Scenarios from Specification Understanding (Apple)
apple_ml- New paperPaperLLMs Are Not (Consistently) Bayesian: Quantifying Internal (In)consistencies of LLMs’ Probabilistic BeliefsApple
New paper: LLMs Are Not (Consistently) Bayesian: Quantifying Internal (In)consistencies of LLMs’ Probabilistic Beliefs (Apple)
apple_ml New paper: REFACTOR-VLA: Unsupervised Library Learning of Typed Motor Programs (Apple)
apple_mlNew paper: SimpleDesign: A Joint Model for Protein Sequence and Structure Codesign (Apple)
apple_ml- New paperPaperPutting Captions to the Test: Evaluating Video Caption Quality through Multiple-Choice Question AnsweringApple
New paper: Putting Captions to the Test: Evaluating Video Caption Quality through Multiple-Choice Question Answering (Apple)
apple_ml
| Source | Document | Type | Tier | Last observed | Snapshots |
|---|---|---|---|---|---|
| Apple Machine Learning Research | machinelearning.apple.com/rss.xml | feed | T1· Official | 21 min ago | 1 |
| GitHub public repositories (HTML, releases.atom, raw files) | github.com/apple-aiml-research/ml-fastvlm | repository | T2· Quality secondary | 11 min ago | 2 |
| Hugging Face Hub (public pages, model cards, papers) | huggingface.co/models?author=apple&p=0&sort=downloads | listing | T2· Quality secondary | 13 min ago | 1 |
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.