BigHugger
Deployability · 202,261 open models

Which models can you actually run?

Every leaderboard ranks models you call over an API. This one ranks models you can put on your own machine — by the runtime that loads them, the format they ship in, whether they're quantised, and whether the licence lets you sell what you build.

Read from the index 2026-09-18

Two different claims sit behind every bar, and they are kept apart everywhere on this page. Declared means a model card named the runtime. By format means the weights are in a container that runtime reads — which says the file will open, not that the architecture is implemented. A model is counted once if either is true. Nothing declares candle, burn or ort; no one writes a Rust runtime on a model card. That gap is the whole reason this page exists.

Reach, by runtime

🦀 burn113,832
mlx11,998
llama.cpp76,048
vllm110,181
091,046182,092 models

declared on the model cardnot declared, but ships a format it reads

Every bar but one is almost entirely light, which is the finding: for most runtimes the evidence is the file, not the card. MLX is the exception — 11,788 cards name it against 471 models shipping an npz, because mlx-community publishes converted weights under a name that says MLX rather than in the format that proves it. It is the one runtime where the card is the better evidence.

The most-used models coreml can load

Either signal
355
Declared
121
By format
350
Commercial use ok
225
Quantised build
43
ModelDownloadsParamsQuantLicenceTerms
google-bert/bert-base-uncased
fill-mask
47,693,504110MApache-2.0commercial ok
argmaxinc/whisperkit-coreml declared
automatic-speech-recognition
11,230,874MITcommercial ok
distilbert/distilgpt2
text-generation
2,083,33888MApache-2.0commercial ok
thenlper/gte-small
sentence-similarity
1,068,65933MMITcommercial ok
jinaai/jina-embeddings-v2-small-en
feature-extraction
928,48433MApache-2.0commercial ok
jinaai/jina-embeddings-v2-base-en
feature-extraction
391,530137MApache-2.0commercial ok
FluidInference/parakeet-tdt-0.6b-v3-coreml declared
automatic-speech-recognition
288,503627M
base model
CC-BY-4.0commercial ok
FluidInference/parakeet-ctc-110m-coreml
automatic-speech-recognition
96,360110M
name
CC-BY-4.0commercial ok
Falconsai/text_summarization
summarization
53,36061MApache-2.0commercial ok
openbmb/MiniCPM-o-4_5-gguf
any-to-any
44,5459.4B
base model
4–16-bit
11 builds
Apache-2.0commercial ok
Barrymanalow/nb-whisper-coreml
automatic-speech-recognition
41,974242M
base model
Apache-2.0commercial ok
argmaxinc/speakerkit-coreml
automatic-speech-recognition
41,206CC-BY-4.0commercial ok
distilbert/distilbert-base-uncased-distilled-squad
question-answering
37,85366MApache-2.0commercial ok
aufklarer/Parakeet-TDT-v3-CoreML-INT8-iOS-5s34,4398-bitCC-BY-4.0commercial ok
tiiuae/falcon-7b-instruct
text-generation
31,8007.2BApache-2.0commercial ok
FluidInference/silero-vad-coreml declared
voice-activity-detection
30,516MITcommercial ok
FluidInference/speaker-diarization-coreml
voice-activity-detection
19,800CC-BY-4.0commercial ok
aufklarer/Chatterbox-Flash-CoreML
text-to-speech
15,095MITcommercial ok
FluidInference/parakeet-tdt-0.6b-v2-coreml
automatic-speech-recognition
12,320600M
name
CC-BY-4.0commercial ok
Gustavosta/MagicPrompt-Stable-Diffusion
text-generation
10,953137MMITcommercial ok
aufklarer/Silero-VAD-v5-CoreML
voice-activity-detection
10,760MITcommercial ok
aufklarer/Parakeet-TDT-v3-CoreML-INT89,5268-bitCC-BY-4.0commercial ok
unum-cloud/uform3-image-text-multilingual-base
feature-extraction
6,359Apache-2.0commercial ok
BarathwajAnandan/cohere-transcribe-03-2026-CoreML-6bit declared
automatic-speech-recognition
5,2302.1B
base model
6-bitGPL-3.0-onlycommercial ok
openbmb/MiniCPM-V-4-gguf
image-text-to-text
4,2644.1B
base model
4–16-bit
11 builds
Apache-2.0commercial ok
aufklarer/DeepFilterNet3-CoreML declared
audio-to-audio
3,737Apache-2.0commercial ok
aufklarer/Kokoro-82M-CoreML declared
text-to-speech
3,69182M
name
Apache-2.0commercial ok
aufklarer/Pyannote-Community-1-CoreML
audio-classification
3,588CC-BY-4.0commercial ok
mattmireles/kokoro-coreml declared
text-to-speech
2,777Apache-2.0commercial ok
gety-ai/gety-embed-v0
sentence-similarity
2,499118M
base model
MITcommercial ok
FluidInference/diar-streaming-sortformer-coreml declared
automatic-speech-recognition
2,436CC-BY-4.0commercial ok
FluidInference/kokoro-82m-coreml
text-to-speech
2,34482M
name
Apache-2.0commercial ok
aufklarer/WeSpeaker-ResNet34-LM-CoreML
audio-classification
2,217MITcommercial ok
aufklarer/Omnilingual-ASR-CTC-300M-CoreML-INT8-10s declared
automatic-speech-recognition
2,139300M
name
8-bitApache-2.0commercial ok
TheStageAI/thewhisper-large-v3-turbo declared
automatic-speech-recognition
1,769809MCC-BY-4.0commercial ok
FluidInference/parakeet-unified-en-0.6b-coreml declared
automatic-speech-recognition
1,740600M
name
CC-BY-4.0commercial ok
aufklarer/Sidon-CoreML declared
audio-to-audio
1,701580M
base model
MITcommercial ok
apple/coreml-depth-anything-v2-small declared
depth-estimation
1,614Apache-2.0commercial ok
FluidInference/pocket-tts-coreml declared
text-to-speech
1,506CC-BY-4.0commercial ok
kensora/kokoro-coreml declared
text-to-speech
1,482Apache-2.0commercial ok
Falconsai/medical_summarization
summarization
1,32661MApache-2.0commercial ok
DictionLabs/whisperkit-coreml
automatic-speech-recognition
1,28373M
base model
MITcommercial ok
mickekringai/kb-whisper-coreml
automatic-speech-recognition
1,046Apache-2.0commercial ok
aufklarer/Silero-VAD-v6.2.1-CoreML declared
voice-activity-detection
1,024MITcommercial ok
yslinear/kotoba-whisper-v2.2-coreml
automatic-speech-recognition
984756M
base model
Apache-2.0commercial ok
aufklarer/Sortformer-Diarization-CoreML declared
audio-classification
809CC-BY-4.0commercial ok
aufklarer/Qwen3-ASR-CoreML
automatic-speech-recognition
752938M
base model
Apache-2.0commercial ok
apple/coreml-sam2.1-tiny declared
mask-generation
719Apache-2.0commercial ok
FluidInference/parakeet-tdt-ctc-110m-coreml
automatic-speech-recognition
674110M
name
CC-BY-4.0commercial ok
mweinbach/Kokoro-82M-Swift
text-to-speech
66182M
name
Apache-2.0commercial ok
takanori-ishikawa/Qwen3.5-ANE-CoreML
text-generation
649873M
base model
Apache-2.0commercial ok
apple/coreml-sam2.1-baseplus declared
mask-generation
514Apache-2.0commercial ok
Writer/palmyra-small
text-generation
490176MApache-2.0commercial ok
aufklarer/Whisper-Large-v3-Turbo-CoreML declared
automatic-speech-recognition
4411.5B
base model
MITcommercial ok
mlboydaisuke/qwen3.5-0.8B-CoreML declared
text-generation
431873M
base model
Apache-2.0commercial ok
aufklarer/Qwen3-ForcedAligner-0.6B-CoreML-INT8
audio-classification
412918M
base model
8-bitApache-2.0commercial ok
apple/coreml-detr-semantic-segmentation declared
image-segmentation
397Apache-2.0commercial ok
mlboydaisuke/qwen3.5-2B-CoreML declared
text-generation
3942.3B
base model
Apache-2.0commercial ok
niduank/Qwen2.5-0.5B-Instruct-ANE-int8 declared392494M
base model
8-bitApache-2.0commercial ok
apple/coreml-depth-anything-small declared
depth-estimation
379Apache-2.0commercial ok

Ordered by downloads, which on these 202,261 models is a real signal — 96% have a non-zero count. Parameter counts are resolved, not just read: the card first, then the base model's card, then the number in the name, then the GGUF file size, which is a per-parameter figure. That sizes 207 of the 355 models coreml can load; the source is printed under every count that did not come from the card itself. Quantisation is read the same way: the card's quant_bits or method where stated, otherwise the GGUF builds the repository actually ships, which is where a range like 2–16-bit and a build count come from.

The licence column resolved in full is on what you're allowed to ship. Everything here is queryable through the API.