1,058 models · refreshed nightly
Models that run on Mac M3 · 24 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 M3 · 24 GB |
|---|---|---|---|---|---|---|
| 301 | xlm-roberta-base-language-detection | 280 M | 512 | ✓ mit | 557 K | 1.8 GB |
| 302 | rtdetr_v2_r18vd | 20 M | — | ✓ apache-2.0 | 557 K | 0.6 GB |
| 303 | phi-2 | 2.8 B | 2 K | ✓ mit | 556 K | 7.0 GB |
| 304 | wav2vec2-xls-r-300m-cv7-turkish | 300 M | — | ✓ cc-by-4.0 | 556 K | 1.2 GB |
| 305 | inclusively-classification | 110 M | 512 | ✗ cc-by-nc-sa-4.0 | 552 K | 1.0 GB |
| 306 | paraphrase-albert-small-v2 | 10 M | 512 | ✓ apache-2.0 | 551 K | 0.6 GB |
| 307 | macbert4csc-base-chinese | 100 M | 512 | ✓ apache-2.0 | 543 K | 1.0 GB |
| 308 | gpt-oss-20b-GGUF | — | 131 K | ✓ apache-2.0 | 543 K | 13.1 GB |
| 309 | resnet-50 | 30 M | — | ✓ apache-2.0 | 542 K | 0.6 GB |
| 310 | ko-sroberta-multitask | 110 M | 512 | unknown | 540 K | 1.0 GB |
| 311 | gpt-neo-125m | 150 M | 2 K | ✓ mit | 538 K | 1.1 GB |
| 312 | whisper-bemba-stt | 240 M | — | unknown | 534 K | 1.6 GB |
| 313 | Qwen3-Embedding-4B-W4A16-G128 | 4.1 B | 41 K | ✓ apache-2.0 | 532 K | 4.0 GB |
| 314 | whisper-medium-gguf | — | — | ✓ apache-2.0 | 529 K | 1.1 GB |
| 315 | Huihui-DeepSeek-V4-Flash-0731-abliterated-GGUF | — | — | ✓ mit | 526 K | 12.5 GB |
| 316 | Qwen3-VL-Embedding-8B-FP8 | 8.8 B | — | ✓ apache-2.0 | 525 K | 13.5 GB |
| 317 | Ornith-1.0-9B-GGUF | — | — | ✓ mit | 520 K | 5.3 GB |
| 318 | distil-large-v3 | 760 M | — | ✓ mit | 517 K | 5.6 GB |
| 319 | jina-embeddings-v5-text-nano | 210 M | 8 K | ✗ cc-by-nc-4.0 | 515 K | 1.1 GB |
| 320 | qwen3-4b-base-dapo-v4 | 4.0 B | 33 K | ✓ apache-2.0 | 515 K | 10.0 GB |
| 321 | Qwen2.5-Coder-7B-Instruct-GPTQ-Int4 | 7.6 B | 33 K | ✓ apache-2.0 | 515 K | 7.8 GB |
| 322 | open-vakgyata | 60 M | — | ✗ cc-by-nc-4.0 | 507 K | 0.8 GB |
| 323 | bloom-560m | 560 M | — | ⚠ bigscience-bloom-rail-1.0 | 502 K | 1.8 GB |
| 324 | wav2vec2-xls-r-300m-sk-cv8 | 300 M | — | ✓ apache-2.0 | 502 K | 1.2 GB |
| 325 | lambda | — | — | unknown | 498 K | 0.5 GB |
| 326 | VibeVoice-1.5B | 2.7 B | — | ✓ mit | 497 K | 6.9 GB |
| 327 | snowflake-arctic-embed-s | 30 M | 512 | ✓ apache-2.0 | 496 K | 0.7 GB |
| 328 | pythia-160m-deduped | 210 M | 2 K | ✓ apache-2.0 | 492 K | 0.9 GB |
| 329 | ruri-v3-310m | 310 M | 8 K | ✓ apache-2.0 | 492 K | 1.9 GB |
| 330 | resnet34.a1_in1k | 20 M | — | ✓ apache-2.0 | 492 K | 0.6 GB |
| 331 | sat-3l-sm | 210 M | 514 | ✓ mit | 491 K | 1.5 GB |
| 332 | cryptobert | 120 M | 512 | ✓ mit | 483 K | 1.1 GB |
| 333 | resnet18.a3_in1k | 10 M | — | ✓ apache-2.0 | 483 K | 0.6 GB |
| 334 | gemma-4-12B-coder-fable5-composer2.5-v1-GGUF | — | — | ✓ apache-2.0 | 483 K | 5.8 GB |
| 335 | SmolLM2-360M | 360 M | 8 K | ✓ apache-2.0 | 481 K | 1.4 GB |
| 336 | snowflake-arctic-embed-l | 334 M | 512 | ✓ apache-2.0 | 480 K | 2.0 GB |
| 337 | Parable-Qwen3-4B-Claude-Fable-5-GGUF | — | — | ✓ apache-2.0 | 479 K | 3.2 GB |
| 338 | Qwen3-4B-GGUF | — | 41 K | ✓ apache-2.0 | 474 K | 2.3 GB |
| 339 | sentence-bert-base-ja-mean-tokens-v2 | 110 M | 512 | cc-by-sa-4.0 | 474 K | 1.0 GB |
| 340 | wav2vec2-large-xlsr-japanese-hiragana | 320 M | — | ✓ apache-2.0 | 472 K | 1.9 GB |
| 341 | wav2vec2-large-xls-r-300m-sinhala-low-LR-part1 | 320 M | — | unknown | 469 K | 1.9 GB |
| 342 | wav2vec2-large-xlsr-53-basque | 320 M | — | ✓ apache-2.0 | 468 K | 1.9 GB |
| 343 | msmarco-distilbert-base-tas-b | 66 M | 512 | ✓ apache-2.0 | 463 K | 0.8 GB |
| 344 | DeepSeek-Coder-V2-Lite-Instruct-GGUF | — | — | other | 461 K | 7.1 GB |
| 345 | pplx-embed-v1-0.6b | 600 M | 33 K | ✓ mit | 461 K | 3.2 GB |
| 346 | mimi | 100 M | 8 K | ✓ cc-by-4.0 | 458 K | 0.9 GB |
| 347 | MedCPT-Query-Encoder | 110 M | 512 | other | 454 K | 1.0 GB |
| 348 | vietnamese-bi-encoder | 130 M | 256 | ✓ apache-2.0 | 454 K | 1.1 GB |
| 349 | indic-conformer-600m-multilingual | 600 M | — | ✓ mit | 453 K | 1.9 GB |
| 350 | vit_base_patch16_224.augreg2_in21k_ft_in1k | 90 M | — | ✓ apache-2.0 | 450 K | 0.9 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.