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 |
|---|---|---|---|---|---|---|
| 551 | vlt5-base-keywords | 280 M | — | ✓ cc-by-4.0 | 223 K | 1.8 GB |
| 552 | gemma-4-12b-heretic-abliterated-GGUF | — | — | ✓ apache-2.0 | 219 K | 0.7 GB |
| 553 | Gemma-4-E4B-DECKARD-HERETIC-NVFP4 | 6.2 B | — | ⚠ gemma | 217 K | 12.6 GB |
| 554 | Meta-Llama-3.1-8B-FP8 | 8.0 B | 131 K | ⚠ llama3.1 | 216 K | 11.7 GB |
| 555 | Mistral-7B-Instruct-v0.1 | 7.2 B | 33 K | ✓ apache-2.0 | 216 K | 17.5 GB |
| 556 | animagine-xl-4.0 | 2.6 B | — | ⚠ openrail++ | 215 K | 23.8 GB |
| 557 | GLM-4.7-Flash-AWQ | 31.2 B | 203 K | ✓ mit | 214 K | 26.9 GB |
| 558 | OpenMed-NER-PharmaDetect-SuperClinical-434M | 430 M | 512 | ✓ apache-2.0 | 214 K | 1.5 GB |
| 559 | dvine82-xl | 2.6 B | — | unknown | 213 K | 8.5 GB |
| 560 | SmolLM2-1.7B-Instruct | 1.7 B | 8 K | ✓ apache-2.0 | 213 K | 4.5 GB |
| 561 | RealVisXL_V5.0 | 2.6 B | — | ⚠ openrail++ | 212 K | 46.7 GB |
| 562 | Mistral-7B-Instruct-v0.3-AWQ | 7.3 B | 33 K | ✓ apache-2.0 | 212 K | 6.2 GB |
| 563 | IP-Adapter-FaceID | — | — | unknown | 210 K | 1.5 GB |
| 564 | t5-large | 740 M | — | ✓ apache-2.0 | 210 K | 3.9 GB |
| 565 | GLM-4.7-Flash-MLX-8bit | 29.9 B | 203 K | ✓ mit | 209 K | 40.0 GB |
| 566 | Llama-2-13b-chat-hf | 13.0 B | — | ⚠ llama2 | 207 K | 31.1 GB |
| 567 | Ornith-1.0-35B-GGUF | — | — | ✓ mit | 203 K | 12.1 GB |
| 568 | xflux_text_encoders | 4.8 B | — | ✓ apache-2.0 | 203 K | 11.7 GB |
| 569 | Qwen2.5-Coder-1.5B | 1.5 B | 33 K | ✓ apache-2.0 | 200 K | 4.1 GB |
| 570 | gemma-1.1-2b-it | 2.5 B | — | ⚠ gemma | 200 K | 6.4 GB |
| 571 | DeepSeek-Coder-V2-Lite-Instruct-FP8 | 15.7 B | 164 K | other | 200 K | 20.6 GB |
| 572 | Qwen2.5-1.5B-Instruct-GGUF | — | — | ✓ apache-2.0 | 199 K | 1.3 GB |
| 573 | Qwen3-Coder-Next-GGUF | — | — | ✓ apache-2.0 | 199 K | 47.4 GB |
| 574 | Qwen1.5-0.5B-Chat | 620 M | 33 K | other | 199 K | 2.0 GB |
| 575 | aya-expanse-8b-AWQ | 9.1 B | 8 K | gpl-3.0 | 198 K | 10.5 GB |
| 576 | Qwen3-4B-Thinking-2507-FP8 | 4.4 B | 262 K | ✓ apache-2.0 | 197 K | 6.9 GB |
| 577 | Qwen2.5-Coder-32B-Instruct-GGUF | — | — | ✓ apache-2.0 | 197 K | 9.1 GB |
| 578 | PowerLM-3b | 3.5 B | 4 K | ✓ apache-2.0 | 195 K | 16.5 GB |
| 579 | GLM-4.7-Flash-MLX-6bit | 29.9 B | 203 K | ✓ mit | 194 K | 31.8 GB |
| 580 | Qwen1.5-MoE-A2.7B | 14.3 B | 8 K | other | 193 K | 34.1 GB |
| 581 | OLMoE-1B-7B-0924 | 6.9 B | 4 K | ✓ apache-2.0 | 192 K | 16.8 GB |
| 582 | talkie-1930-13b-it-hf | 13.3 B | 2 K | ✓ apache-2.0 | 191 K | 31.7 GB |
| 583 | pythia-160m-deduped | 210 M | 2 K | ✓ apache-2.0 | 191 K | 0.9 GB |
| 584 | Qwen2.5-Coder-7B-Instruct-GGUF | — | — | ✓ apache-2.0 | 189 K | 3.8 GB |
| 585 | Llama-3.2-3B-Instruct | 3.2 B | 131 K | ⚠ llama3.2 | 188 K | 8.0 GB |
| 586 | gemma4-e4b-claims-comparison | 7.9 B | — | ⚠ gemma | 188 K | 19.2 GB |
| 587 | Phi-mini-MoE-instruct | 7.7 B | 4 K | ✓ mit | 186 K | 18.5 GB |
| 588 | Qwen3-0.6B-GGUF | — | — | unknown | 186 K | 0.9 GB |
| 589 | Sugoi-14B-Ultra-GGUF | — | — | ✓ apache-2.0 | 185 K | 6.8 GB |
| 590 | Laguna-S-2.1-GGUF | — | — | openmdw-1.1 | 185 K | 37.6 GB |
| 591 | llava-onevision-qwen2-7b-ov | 8.0 B | 33 K | ✓ apache-2.0 | 185 K | 19.4 GB |
| 592 | Qwen2.5-3B-Instruct-GGUF | — | — | other | 185 K | 2.0 GB |
| 593 | Qwen3-14B-GGUF | — | — | unknown | 184 K | 6.8 GB |
| 594 | Qwen3-8B | 8.2 B | 41 K | ✓ apache-2.0 | 183 K | 19.7 GB |
| 595 | openai-gpt | 120 M | — | ✓ mit | 183 K | 1.0 GB |
| 596 | novaAnimeXL_ilV140 | 2.6 B | — | unknown | 183 K | 16.1 GB |
| 597 | Qwen3-4B-unsloth-bnb-4bit | 4.1 B | 41 K | ✓ apache-2.0 | 183 K | 5.0 GB |
| 598 | Qwen3-14B-unsloth-bnb-4bit | 15.2 B | 41 K | ✓ apache-2.0 | 181 K | 15.0 GB |
| 599 | Qwen2.5-7B-Instruct-GGUF | — | — | ✓ apache-2.0 | 180 K | 3.6 GB |
| 600 | Qwen3-8B-GGUF | — | — | unknown | 180 K | 4.1 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.