1,000 models · refreshed nightly
Models that run on 2 × 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 2 × 24 GB |
|---|---|---|---|---|---|---|
| 451 | MiniCPM5-1B-Claude-Opus-Fable5-Thinking-GGUF | — | — | ✓ apache-2.0 | 344 K | 1.3 GB |
| 452 | gemma-3-270m-it | 270 M | — | ⚠ gemma | 344 K | 1.1 GB |
| 453 | gpt-neo-125m | 150 M | 2 K | ✓ mit | 343 K | 1.1 GB |
| 454 | Llama-2-7b-hf | 6.7 B | 4 K | unknown | 335 K | 16.3 GB |
| 455 | NVIDIA-Nemotron-Nano-12B-v2 | 12.3 B | — | other | 331 K | 29.4 GB |
| 456 | T-lite-it-2.1 | 8.2 B | 41 K | ✓ apache-2.0 | 327 K | 19.7 GB |
| 457 | Mistral-7B-Instruct-v0.2-AWQ | 7.2 B | 33 K | ✓ apache-2.0 | 325 K | 6.2 GB |
| 458 | efficientnet_b2.ra_in1k | 10 M | — | ✓ apache-2.0 | 314 K | 0.5 GB |
| 459 | edgenext_small.usi_in1k | 10 M | — | ✓ mit | 313 K | 0.5 GB |
| 460 | granite-4.1-3b | 3.4 B | 131 K | ✓ apache-2.0 | 312 K | 8.5 GB |
| 461 | NVIDIA-Nemotron-Nano-9B-v2 | 8.9 B | 131 K | other | 310 K | 21.4 GB |
| 462 | RMBG-1.4 | 40 M | — | other | 310 K | 0.7 GB |
| 463 | segformer_b2_clothes | 30 M | — | other | 308 K | 0.6 GB |
| 464 | voice-gender-classifier | 20 M | — | ✓ mit | 307 K | 0.6 GB |
| 465 | Jan-v3.5-4B-gguf | — | — | ✓ apache-2.0 | 306 K | 2.8 GB |
| 466 | Qwen2.5-3B | 3.1 B | 33 K | other | 306 K | 7.8 GB |
| 467 | xlm-roberta-base-ner-hrl | 280 M | 512 | ✓ afl-3.0 | 304 K | 1.8 GB |
| 468 | Olmo-3-7B-Instruct-SFT | 7.3 B | 66 K | ✓ apache-2.0 | 301 K | 17.7 GB |
| 469 | phishing-email-detection-distilbert_v2.4.1 | 70 M | 512 | ✓ apache-2.0 | 301 K | 0.8 GB |
| 470 | Qwen2-0.5B-Instruct | 490 M | 33 K | ✓ apache-2.0 | 294 K | 1.7 GB |
| 471 | Meta-Llama-3.1-8B-Instruct-GGUF | — | — | ⚠ llama3.1 | 294 K | 3.7 GB |
| 472 | mms-lid-126 | 970 M | — | ✗ cc-by-nc-4.0 | 291 K | 4.9 GB |
| 473 | deberta-v3-base-prompt-injection-v2 | 180 M | 512 | ✓ apache-2.0 | 291 K | 1.3 GB |
| 474 | CommunityForensics-DeepfakeDet-ViT | 40 M | — | ✓ mit | 290 K | 0.7 GB |
| 475 | Meta-Llama-3-8B | 8.0 B | 8 K | other | 290 K | 19.4 GB |
| 476 | rtdetr_v2_r18vd | 20 M | — | ✓ apache-2.0 | 289 K | 0.6 GB |
| 477 | SmolLM-135M | 130 M | 2 K | ✓ apache-2.0 | 288 K | 1.1 GB |
| 478 | DeepSeek-R1-Distill-Qwen-7B | 7.6 B | 131 K | ✓ mit | 288 K | 18.4 GB |
| 479 | Llama-3.2-1B-Instruct | 1.2 B | 131 K | ⚠ llama3.2 | 287 K | 3.4 GB |
| 480 | MuQ-large-msd-iter | 330 M | — | ✗ cc-by-nc-4.0 | 286 K | 2.0 GB |
| 481 | gemma-4-12B-coder-fable5-composer2.5-v1-GGUF | — | — | ✓ apache-2.0 | 286 K | 5.8 GB |
| 482 | roberta-large-mnli | 360 M | 512 | ✓ mit | 285 K | 2.1 GB |
| 483 | llama-7b | 6.7 B | 2 K | other | 285 K | 16.3 GB |
| 484 | MiMo-7B-Base | 7.8 B | 33 K | ✓ mit | 284 K | 18.9 GB |
| 485 | vit_small_patch16_224.augreg_in21k_ft_in1k | 20 M | — | ✓ apache-2.0 | 283 K | 0.6 GB |
| 486 | Qwen2.5-7B-Instruct-GPTQ-Int4 | 7.6 B | 33 K | ✓ apache-2.0 | 282 K | 7.8 GB |
| 487 | nsfw-classifier | 90 M | — | ✗ cc-by-nc-nd-4.0 | 279 K | 0.9 GB |
| 488 | granite-4.0-h-tiny | 6.9 B | 131 K | ✓ apache-2.0 | 279 K | 16.8 GB |
| 489 | DeepSeek-R1-0528-Qwen3-8B-MLX-4bit | 1.3 B | 131 K | ✓ mit | 278 K | 5.8 GB |
| 490 | Qwen3-8B-GGUF | — | 41 K | ✓ apache-2.0 | 277 K | 4.1 GB |
| 491 | open-vakgyata | 60 M | — | ✗ cc-by-nc-4.0 | 274 K | 0.8 GB |
| 492 | Qwen3-4B-GGUF | — | — | ✓ apache-2.0 | 274 K | 3.2 GB |
| 493 | MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking-GGUF | — | — | ✓ apache-2.0 | 265 K | 1.8 GB |
| 494 | Qwen2.5-Math-1.5B | 1.5 B | 4 K | ✓ apache-2.0 | 265 K | 4.1 GB |
| 495 | madlad400-3b-mt | 2.9 B | — | ✓ apache-2.0 | 263 K | 2.8 GB |
| 496 | gemma-2-2b | 2.6 B | — | ⚠ gemma | 263 K | 12.4 GB |
| 497 | wikineural-multilingual-ner | 180 M | 512 | ✗ cc-by-nc-sa-4.0 | 263 K | 1.3 GB |
| 498 | gemma-4-12B-agentic-fable5-composer2.5-v2-3.5x-tau2 | 12.0 B | — | ✓ apache-2.0 | 260 K | 28.6 GB |
| 499 | DeepSeek-R1-0528-Qwen3-8B-MLX-8bit | 2.3 B | 131 K | ✓ mit | 258 K | 10.4 GB |
| 500 | plant-identity | 90 M | — | unknown | 257 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.