1,000 models · refreshed nightly
Models that run on Mac M4 Max · 64 GB
Every model in the catalog with its licence, estimated VRAM and daily-tracked downloads. Filters update the URL — share any view.
| # | Model | Params | Context | Commercial use | 30d | On Mac M4 Max · 64 GB |
|---|---|---|---|---|---|---|
| 251 | Qwen3.6-35B-A3B-NVFP4 | 34.7 B | — | ✓ apache-2.0 | 975 K | 33.2 GB |
| 252 | wav2vec2-large-xlsr-korean | 320 M | — | ✓ apache-2.0 | 971 K | 1.9 GB |
| 253 | Qwen3-Coder-30B-A3B-Instruct-AWQ-4bit | 5.3 B | 262 K | ✓ apache-2.0 | 968 K | 21.2 GB |
| 254 | Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-V12-GGUF | — | — | ✓ apache-2.0 | 965 K | 29.9 GB |
| 255 | roberta-base-go_emotions | 120 M | 512 | ✓ mit | 962 K | 1.1 GB |
| 256 | cohere-transcribe-03-2026-gguf | — | — | ✓ apache-2.0 | 961 K | 2.2 GB |
| 257 | Qwen3.6-27B-AWQ-INT4 | 29.3 B | — | ✓ apache-2.0 | 952 K | 27.4 GB |
| 258 | gemma-4-26B-A4B-it-GGUF | — | — | ✓ apache-2.0 | 952 K | 11.4 GB |
| 259 | gemma-4-26B-A4B-it-FP8-dynamic | 26.5 B | — | ✓ apache-2.0 | 948 K | 36.0 GB |
| 260 | F5-TTS | — | — | ✗ cc-by-nc-4.0 | 946 K | 5.0 GB |
| 261 | Ornith-1.0-35B-FP8 | 35.1 B | — | ✓ mit | 945 K | 47.2 GB |
| 262 | privacy-filter-nemotron-GGUF | — | — | ✓ apache-2.0 | 944 K | 2.3 GB |
| 263 | wav2vec2-xls-r-300m-ftspeech | 320 M | — | other | 944 K | 1.9 GB |
| 264 | pubmedbert-base-embeddings | 110 M | 512 | ✓ apache-2.0 | 941 K | 1.0 GB |
| 265 | vit-base-nsfw-detector | 90 M | — | ✓ apache-2.0 | 937 K | 0.9 GB |
| 266 | Qwen2.5-Coder-7B-Instruct-AWQ | 7.6 B | 33 K | ✓ apache-2.0 | 930 K | 7.8 GB |
| 267 | Qwen3-4B-Instruct-2507-FP8 | 4.4 B | 262 K | ✓ apache-2.0 | 930 K | 6.9 GB |
| 268 | rtdetr_r101vd_coco_o365 | 80 M | — | ✓ apache-2.0 | 911 K | 0.9 GB |
| 269 | DeepSeek-Coder-V2-Lite-Instruct | 15.7 B | 164 K | other | 911 K | 37.4 GB |
| 270 | repeat | — | — | unknown | 908 K | 0.5 GB |
| 271 | dreamshaper-7 | 860 M | — | ⚠ creativeml-openrail-m | 900 K | 9.7 GB |
| 272 | snowflake-arctic-embed-l-v2.0 | 570 M | 8 K | ✓ apache-2.0 | 889 K | 3.1 GB |
| 273 | sdxl-turbo | 2.6 B | — | other | 886 K | 46.7 GB |
| 274 | Juggernaut-XL-v9 | — | — | ⚠ creativeml-openrail-m | 869 K | 15.9 GB |
| 275 | Llama-3.2-1B | 1.2 B | — | ⚠ llama3.2 | 869 K | 3.4 GB |
| 276 | ced-gguf | — | — | ✓ apache-2.0 | 866 K | 0.6 GB |
| 277 | jina-embeddings-v2-small-en | 30 M | 8 K | ✓ apache-2.0 | 862 K | 0.6 GB |
| 278 | Qwen2.5-1.5B | 1.5 B | 131 K | ✓ apache-2.0 | 860 K | 4.1 GB |
| 279 | DeepSeek-R1-0528-Qwen3-8B | 8.2 B | 131 K | ✓ mit | 858 K | 19.7 GB |
| 280 | deberta-v3-base-prompt-injection-v2 | 180 M | 512 | ✓ apache-2.0 | 852 K | 1.3 GB |
| 281 | opus-mt-fr-en | 80 M | 512 | ✓ apache-2.0 | 848 K | 0.8 GB |
| 282 | wav2vec2-large-xlsr-mvc-swahili | 320 M | — | ✓ apache-2.0 | 845 K | 1.9 GB |
| 283 | e5-base-v2 | 110 M | 512 | ✓ mit | 829 K | 1.0 GB |
| 284 | NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4 | 18.2 B | 262 K | other | 827 K | 24.5 GB |
| 285 | Qwen3-0.6B-Base | 600 M | 33 K | ✓ apache-2.0 | 816 K | 1.9 GB |
| 286 | POCKET-35B-GGUF | — | — | ✓ apache-2.0 | 812 K | 9.6 GB |
| 287 | Qwen3-32B-AWQ | 32.8 B | 41 K | ✓ apache-2.0 | 811 K | 26.7 GB |
| 288 | Llama-2-7b-hf | 6.7 B | — | ⚠ llama2 | 806 K | 16.3 GB |
| 289 | Ornith-1.5-9B-NVFP4 | 6.7 B | — | ✓ mit | 805 K | 11.2 GB |
| 290 | multi-qa-MiniLM-L6-cos-v1 | 20 M | 512 | unknown | 805 K | 0.6 GB |
| 291 | OLMo-2-0425-1B | 1.5 B | 4 K | ✓ apache-2.0 | 799 K | 7.3 GB |
| 292 | Qwen3.8-4B-Distill-GGUF | — | — | ✓ apache-2.0 | 793 K | 3.6 GB |
| 293 | Qwen3-8B-FP8 | 8.2 B | 41 K | ✓ apache-2.0 | 780 K | 12.1 GB |
| 294 | rorshark-vit-base | 90 M | — | ✓ apache-2.0 | 777 K | 0.9 GB |
| 295 | Qwen3.8-2B-Distill-GGUF | — | — | ✓ apache-2.0 | 772 K | 1.9 GB |
| 296 | efficientnet_b0.ra_in1k | 10 M | — | ✓ apache-2.0 | 761 K | 0.5 GB |
| 297 | yolos-small | 30 M | — | ✓ apache-2.0 | 760 K | 0.6 GB |
| 298 | pythia-6.9b | 7.0 B | 2 K | ✓ apache-2.0 | 754 K | 16.8 GB |
| 299 | nemotron-3.5-asr-streaming-0.6b | 640 M | — | other | 752 K | 1.4 GB |
| 300 | gemma-2-9b-it | 9.2 B | — | ⚠ gemma | 745 K | 22.2 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.