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 2026-09-18Two 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
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 mlx can load
- Either signal
- 11,998
- Declared
- 11,664
- By format
- 486
- Commercial use ok
- 8,169
- Quantised build
- 9,315
| Model | Downloads | Params | Quant | Licence | Terms |
|---|---|---|---|---|---|
| pyannote/speaker-diarization-community-1 declared automatic-speech-recognition | 5,091,365 | — | — | CC-BY-4.0 | commercial ok |
| mlx-community/parakeet-tdt-0.6b-v3 declared automatic-speech-recognition | 1,828,956 | 627M | — | CC-BY-4.0 | commercial ok |
| OBLITERATUS/Qwen3.8-27B-OBLITERATED declared text-generation | 1,295,697 | 28B | 2–16-bit 8 builds | Apache-2.0 | commercial ok |
| mlx-community/parakeet-tdt-0.6b-v2 declared automatic-speech-recognition | 1,279,723 | 618M | — | CC-BY-4.0 | commercial ok |
| prism-ml/Bonsai-27B-mlx-1bit declared text-generation | 1,057,283 | 1.7B | — | Apache-2.0 | commercial ok |
| prism-ml/Ternary-Bonsai-27B-mlx-2bit declared text-generation | 1,047,631 | 27B | 2-bit | Apache-2.0 | commercial ok |
| mlx-community/Llama-3.1-8B-Instruct-4bit declared text-generation | 1,038,658 | 8.0B | 4-bit | — | conditional |
| pnnbao-ump/VieNeu-TTS-v3-Turbo text-to-speech | 584,396 | 131M | — | Apache-2.0 | commercial ok |
| ggml-org/models-moved | 516,130 | 7.2B gguf size | 3–16-bit 4 builds | — | unknown |
| ornith-ai/Ornith-1.5-35B-A3B-MLX declared text-generation | 341,893 | 35B | — | — | unknown |
| ornith-ai/Ornith-1.5-9B-MLX declared text-generation | 300,703 | 9.0B | — | — | unknown |
| ornith-ai/Ornith-1.5-9B-MLX-8bit declared text-generation | 300,181 | 9.0B | 8-bit | — | unknown |
| lmstudio-community/DeepSeek-R1-0528-Qwen3-8B-MLX-4bit declared text-generation | 292,612 | 8.2B | 4-bit | MIT | commercial ok |
| mlx-community/gpt-oss-20b-MXFP4-Q8 declared text-generation | 284,933 | 21B | 4-bit | Apache-2.0 | commercial ok |
| lmstudio-community/DeepSeek-R1-0528-Qwen3-8B-MLX-8bit declared text-generation | 270,776 | 8.2B | 8-bit | MIT | commercial ok |
| mlx-community/Qwen2.5-Coder-7B-Instruct-4bit declared text-generation | 258,747 | 7.6B | 4-bit | Apache-2.0 | commercial ok |
| ornith-ai/Ornith-1.5-9B-MLX-4bit declared text-generation | 252,606 | 9.0B | 4-bit | — | unknown |
| mlx-community/gemma-3-12b-it-4bit declared image-text-to-text | 236,200 | 12B base model | 4-bit | — | conditional |
| mlx-community/whisper-small-mlx declared automatic-speech-recognition | 230,145 | — | — | — | unknown |
| mlx-community/Qwen3-ASR-0.6B-8bit declared | 223,023 | 782M | 8-bit | Apache-2.0 | commercial ok |
| mlx-community/whisper-large-v3-turbo declared automatic-speech-recognition | 201,418 | — | — | — | unknown |
| ornith-ai/Ornith-1.5-9B-MLX-6bit declared text-generation | 198,623 | 9.0B | 6-bit | — | unknown |
| ornith-ai/Ornith-1.5-35B-A3B-MLX-4bit declared text-generation | 183,520 | 35B | 4-bit | — | unknown |
| ornith-ai/Ornith-1.5-35B-A3B-MLX-8bit declared text-generation | 180,239 | 35B | 8-bit | — | unknown |
| orcarouter/Qwen3.8-27B-Uncensored-MLX declared image-text-to-text | 176,359 | 27B | 4-bit | Apache-2.0 | commercial ok |
| pyannote-community/speaker-diarization-community-1 declared automatic-speech-recognition | 169,148 | — | — | CC-BY-4.0 | commercial ok |
| mlx-community/Kimi-K2.5 declared text-generation | 161,997 | 1026B | 4-bit | — | unknown |
| ornith-ai/Ornith-1.5-35B-A3B-MLX-6bit declared text-generation | 154,682 | 35B | 6-bit | — | unknown |
| lmstudio-community/Qwen3-VL-8B-Instruct-MLX-5bit declared image-text-to-text | 148,265 | 8.8B base model | 5-bit | Apache-2.0 | commercial ok |
| ampixa/sanoTTS text-to-speech | 141,331 | 294,279 gguf size | — | GPL-3.0-only | commercial ok |
| lmstudio-community/Qwen2.5-Coder-14B-Instruct-MLX-4bit declared text-generation | 128,092 | 15B | 4-bit | Apache-2.0 | commercial ok |
| mlx-community/Qwen3.8-27B-4bit declared image-text-to-text | 126,324 | 27B | 4-bit | Apache-2.0 | commercial ok |
| lmstudio-community/Qwen3-Coder-Next-MLX-8bit declared | 126,131 | 80B | 8-bit | Apache-2.0 | commercial ok |
| lmstudio-community/Qwen3-Coder-Next-MLX-4bit declared | 115,173 | 80B | 4-bit | Apache-2.0 | commercial ok |
| lmstudio-community/Qwen3-Coder-Next-MLX-6bit declared | 112,420 | 80B | 6-bit | Apache-2.0 | commercial ok |
| lmstudio-community/Qwen2.5-Coder-14B-Instruct-MLX-8bit declared text-generation | 110,842 | 15B | 8-bit | Apache-2.0 | commercial ok |
| lmstudio-community/Qwen3-VL-4B-Instruct-MLX-4bit declared image-text-to-text | 109,814 | 4.4B | 4-bit | Apache-2.0 | commercial ok |
| mlx-community/Qwen3-0.6B-8bit declared text-generation | 104,372 | 596M | 8-bit | Apache-2.0 | commercial ok |
| lmstudio-community/Qwen3-VL-4B-Instruct-MLX-6bit declared image-text-to-text | 103,181 | 4.4B | 6-bit | Apache-2.0 | commercial ok |
| lmstudio-community/Qwen3-VL-4B-Instruct-MLX-8bit declared image-text-to-text | 103,008 | 4.4B | 8-bit | Apache-2.0 | commercial ok |
| lmstudio-community/Qwen3-VL-4B-Instruct-MLX-5bit declared image-text-to-text | 102,472 | 4.4B | 5-bit | Apache-2.0 | commercial ok |
| mlx-community/Devstral-Small-2-24B-Instruct-2512-4bit declared image-text-to-text | 98,931 | 24B | 4-bit | Apache-2.0 | commercial ok |
| lmstudio-community/Qwen3-VL-8B-Instruct-MLX-4bit declared image-text-to-text | 97,372 | 8.8B base model | 4-bit | Apache-2.0 | commercial ok |
| lmstudio-community/Qwen3-VL-8B-Instruct-MLX-8bit declared image-text-to-text | 94,237 | 8.8B base model | 8-bit | Apache-2.0 | commercial ok |
| nvidia/GR00T-N1.7-3B robotics | 93,865 | 3.1B | — | — | unknown |
| lmstudio-community/Qwen3-VL-8B-Instruct-MLX-6bit declared image-text-to-text | 92,022 | 8.8B base model | 6-bit | Apache-2.0 | commercial ok |
| mlx-community/all-MiniLM-L6-v2-4bit declared sentence-similarity | 91,999 | 23M | 4-bit | Apache-2.0 | commercial ok |
| mlx-community/Qwen3-30B-A3B-Instruct-2507-4bit declared text-generation | 90,937 | 31B | 4-bit | Apache-2.0 | commercial ok |
| mlx-community/Kokoro-82M-bf16 declared text-to-speech | 86,450 | 82M name | — | Apache-2.0 | commercial ok |
| mlx-community/Qwen3-8B-4bit declared text-generation | 81,654 | 8.2B | 4-bit | Apache-2.0 | commercial ok |
| HumanCompatibleAI/ppo-seals-CartPole-v0 declared reinforcement-learning | 62,782 | — | — | — | unknown |
| lmstudio-community/Hermes-4-70B-MLX-4bit declared | 60,587 | 71B | 4-bit | — | conditional |
| lmstudio-community/Qwen3-14B-MLX-4bit declared text-generation | 60,340 | 15B | 4-bit | Apache-2.0 | commercial ok |
| Youssofal/Qwen3.8-27B-MTPLX-Optimized-Speed declared text-generation | 58,033 | 27B | 4-bit | Apache-2.0 | commercial ok |
| lmstudio-community/Hermes-4-70B-MLX-8bit declared | 57,004 | 71B | 8-bit | — | conditional |
| lmstudio-community/Hermes-4-70B-MLX-6bit declared | 56,522 | 71B | 6-bit | — | conditional |
| lmstudio-community/Hermes-4-70B-MLX-5bit declared | 56,366 | 71B | 5-bit | — | conditional |
| lmstudio-community/Qwen3-14B-MLX-8bit declared text-generation | 55,234 | 15B | 8-bit | Apache-2.0 | commercial ok |
| mlx-community/gemma-3-4b-it-qat-4bit declared image-text-to-text | 52,459 | 5.0B | 4-bit | — | unknown |
| mlx-community/GLM-OCR-4bit declared image-to-text | 48,699 | 1.1B | 4-bit | MIT | commercial 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 11,612 of the 11,998 models mlx 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.