1,023 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 |
|---|---|---|---|---|---|---|
| 601 | LLaMmlein_1B_prerelease | 1.1 B | 2 K | other | 179 K | 5.5 GB |
| 602 | Pony_Diffusion_V6_XL | — | — | cdla-permissive-2.0 | 179 K | 8.5 GB |
| 603 | Qwen3-1.7B-GGUF | — | — | unknown | 178 K | 1.5 GB |
| 604 | Phi-3-mini-4k-instruct-gptq-4bit | 3.8 B | 4 K | unknown | 178 K | 3.6 GB |
| 605 | Qwen3-32B-GGUF | — | — | unknown | 177 K | 14.1 GB |
| 606 | Qwen3-30B-A3B-GGUF | — | — | unknown | 177 K | 12.9 GB |
| 607 | Juggernaut-XL-v9 | — | — | ⚠ creativeml-openrail-m | 176 K | 15.9 GB |
| 608 | starcoder2-3b | 3.0 B | 16 K | bigcode-openrail-m | 176 K | 14.3 GB |
| 609 | Qwen3-30B-A3B-Thinking-2507-AWQ-4bit | 5.3 B | 262 K | ✓ apache-2.0 | 173 K | 21.2 GB |
| 610 | avibe | 7.9 B | 33 K | ✓ apache-2.0 | 173 K | 19.1 GB |
| 611 | llama-3-8b-instruct-awq | 8.0 B | 8 K | unknown | 173 K | 8.0 GB |
| 612 | Qwen2.5-0.5B-Instruct-GGUF | — | — | ✓ apache-2.0 | 172 K | 1.0 GB |
| 613 | NVIDIA-Nemotron-Nano-9B-v2-FP8 | 8.9 B | 131 K | other | 171 K | 13.1 GB |
| 614 | Qwen3-30B-A3B-FP8 | 30.5 B | 41 K | ✓ apache-2.0 | 171 K | 40.8 GB |
| 615 | granite-4.1-3b-GGUF | — | — | ✓ apache-2.0 | 170 K | 2.0 GB |
| 616 | Qwen3-14B-GPTQ-Int4 | 14.8 B | 41 K | ✓ apache-2.0 | 170 K | 13.7 GB |
| 617 | LFM2.5-8B-A1B | 8.5 B | 128 K | other | 170 K | 20.4 GB |
| 618 | falcon-mamba-7b | 7.3 B | — | other | 170 K | 17.6 GB |
| 619 | Qwen2.5-7B-Instruct-bnb-4bit | 7.8 B | 33 K | ✓ apache-2.0 | 170 K | 7.8 GB |
| 620 | TinyLlama-1.1B-Chat-v0.3-AWQ | 1.1 B | 2 K | ✓ apache-2.0 | 169 K | 1.5 GB |
| 621 | Meta-Llama-3-8B-Instruct | 8.0 B | 8 K | other | 169 K | 19.4 GB |
| 622 | Gemma-4-26B-A4B-it-NVFP4 | 15.1 B | — | ✓ apache-2.0 | 168 K | 20.8 GB |
| 623 | Meta-Llama-3.1-8B-Instruct-AWQ-INT4 | 8.0 B | 131 K | ⚠ llama3.1 | 167 K | 8.0 GB |
| 624 | Qwen3-30B-A3B-GPTQ-Int4 | 30.5 B | 41 K | ✓ apache-2.0 | 167 K | 23.7 GB |
| 625 | Agents-A1-4B | 4.5 B | — | ✓ apache-2.0 | 167 K | 11.2 GB |
| 626 | Qwen2.5-Math-1.5B-Instruct | 1.5 B | 4 K | ✓ apache-2.0 | 167 K | 4.1 GB |
| 627 | RnJ-1-Instruct-FP8 | 8.8 B | 33 K | ⚠ gemma | 164 K | 15.0 GB |
| 628 | Llama-3.2-1B-Instruct-GGUF | — | — | ⚠ llama3.2 | 162 K | 1.2 GB |
| 629 | Qwen3-4B-Instruct-2507-NVFP4 | 2.8 B | 262 K | ✓ apache-2.0 | 161 K | 4.9 GB |
| 630 | stable-diffusion-xl-1.0-inpainting-0.1 | 2.6 B | — | ⚠ openrail++ | 155 K | 23.8 GB |
| 631 | opus-mt-tc-big-tr-en | 230 M | 1 K | ✓ cc-by-4.0 | 154 K | 1.1 GB |
| 632 | animagine-xl-3.1 | 2.6 B | — | ⚠ openrail++ | 153 K | 16.1 GB |
| 633 | nova-furry-xl-il-v120-sdxl | 2.6 B | — | other | 151 K | 8.5 GB |
| 634 | financial-summarization-pegasus | 570 M | 512 | unknown | 148 K | 3.1 GB |
| 635 | dreamshaper-8 | 860 M | — | ⚠ creativeml-openrail-m | 142 K | 9.7 GB |
| 636 | one-obsession-17-red-sdxl | 2.6 B | — | other | 140 K | 8.5 GB |
| 637 | Hunyuan-MT-7B-GGUF | — | — | unknown | 137 K | 3.1 GB |
| 638 | amanatsu-illustrious-v11-sdxl | 2.6 B | — | other | 135 K | 8.5 GB |
| 639 | stable-diffusion-inpainting | — | — | ⚠ creativeml-openrail-m | 128 K | 3.5 GB |
| 640 | FLUX.1-schnell-gguf | — | — | ✓ apache-2.0 | 126 K | 4.9 GB |
| 641 | LCM_Dreamshaper_v7 | 860 M | — | ✓ mit | 119 K | 10.4 GB |
| 642 | FLUX.1-dev-gguf | — | — | other | 109 K | 4.9 GB |
| 643 | dreamshaper-xl-lightning | 2.6 B | — | ⚠ openrail++ | 100 K | 39.0 GB |
| 644 | controlnet-union-sdxl-1.0 | 1.3 B | — | ✓ apache-2.0 | 97 K | 6.2 GB |
| 645 | Hy-MT2-1.8B | 2.0 B | 262 K | ✓ apache-2.0 | 96 K | 5.3 GB |
| 646 | stable-diffusion-v1-5 | 860 M | — | unknown | 92 K | 8.3 GB |
| 647 | RealVisXL_V4.0 | 2.6 B | — | ⚠ openrail++ | 90 K | 31.4 GB |
| 648 | T5-base-10K-summarization | 220 M | — | unknown | 84 K | 1.5 GB |
| 649 | mbart-large-en-ro | 610 M | 1 K | ✓ mit | 82 K | 1.9 GB |
| 650 | diving-illustrious-real-asian-v50-sdxl | 2.6 B | — | other | 81 K | 8.5 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.