1,000 models · refreshed nightly
Models that run on RTX 3060 · 12 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 RTX 3060 · 12 GB |
|---|---|---|---|---|---|---|
| 401 | MiniCPM5-2B-DSpark | 324 M | 131 K | ✓ apache-2.0 | 275 K | 1.3 GB |
| 402 | Qwen3-14B-GGUF | — | — | unknown | 274 K | 6.8 GB |
| 403 | vit_tiny_r_s16_p8_224.augreg_in21k | 10 M | — | ✓ apache-2.0 | 274 K | 0.5 GB |
| 404 | Qwen3-4B-GGUF | — | — | unknown | 272 K | 2.3 GB |
| 405 | tiny_starcoder_py | 160 M | — | bigcode-openrail-m | 272 K | 1.2 GB |
| 406 | Qwen2.5-Coder-7B-Instruct-GGUF | — | — | ✓ apache-2.0 | 272 K | 3.8 GB |
| 407 | DeepSeek-R1-0528-Qwen3-8B-MLX-8bit | 2.3 B | 131 K | ✓ mit | 271 K | 10.4 GB |
| 408 | CodonTransformer | 90 M | 4 K | ✓ apache-2.0 | 270 K | 0.9 GB |
| 409 | Qwen3-1.7B-GGUF | — | — | unknown | 270 K | 1.5 GB |
| 410 | Qwen3-0.6B-FP8 | 750 M | 41 K | ✓ apache-2.0 | 270 K | 1.8 GB |
| 411 | FLUX.1-dev-gguf | — | — | other | 269 K | 4.9 GB |
| 412 | Qwen3-8B-GGUF | — | — | unknown | 269 K | 4.1 GB |
| 413 | Qwen3-4B-AWQ | 4.0 B | 41 K | ✓ apache-2.0 | 268 K | 4.0 GB |
| 414 | taardis-27b-full-ternary | — | — | ✓ apache-2.0 | 268 K | 8.4 GB |
| 415 | openai-gpt | 120 M | — | ✓ mit | 265 K | 1.0 GB |
| 416 | llama-3-8b-instruct-awq | 8.0 B | 8 K | unknown | 265 K | 8.0 GB |
| 417 | Apodex-1.1-mini-GGUF | — | — | ✓ apache-2.0 | 264 K | 10.2 GB |
| 418 | Llama-Guard-3-1B | 1.5 B | 131 K | ⚠ llama3.2 | 264 K | 4.0 GB |
| 419 | xlm-roberta-base-ner-hrl | 280 M | 512 | ✓ afl-3.0 | 262 K | 1.8 GB |
| 420 | Llama-3.2-1B-Instruct | 1.2 B | 131 K | ⚠ llama3.2 | 262 K | 3.4 GB |
| 421 | OpenMed-NER-PharmaDetect-SuperClinical-434M | 430 M | 512 | ✓ apache-2.0 | 262 K | 1.5 GB |
| 422 | nsfw-classifier | 90 M | — | ✗ cc-by-nc-nd-4.0 | 260 K | 0.9 GB |
| 423 | Spark-X2.5-4B-GGUF | 4.0 B | — | ✓ apache-2.0 | 259 K | 4.0 GB |
| 424 | Qwen2.5-Coder-7B-Instruct-4bit | 1.2 B | 33 K | ✓ apache-2.0 | 258 K | 5.4 GB |
| 425 | Pony_Diffusion_V6_XL | — | — | cdla-permissive-2.0 | 258 K | 8.5 GB |
| 426 | convnextv2-base-22k-384 | 90 M | — | ✓ apache-2.0 | 253 K | 0.9 GB |
| 427 | bert-small-pii-detection | 30 M | 512 | ✓ apache-2.0 | 252 K | 0.6 GB |
| 428 | Qwen2.5-1.5B-apeach | 1.5 B | 131 K | unknown | 251 K | 7.5 GB |
| 429 | OpenMed-PII-SuperClinical-Small-44M-v1 | 140 M | 512 | ✓ apache-2.0 | 250 K | 1.1 GB |
| 430 | sarashina2.2-0.5b-instruct-v0.1 | 790 M | 8 K | ✓ mit | 248 K | 2.4 GB |
| 431 | SmolLM2-1.7B-Instruct | 1.7 B | 8 K | ✓ apache-2.0 | 247 K | 4.5 GB |
| 432 | convnextv2_large.fcmae_ft_in22k_in1k_384 | 200 M | — | ✗ cc-by-nc-4.0 | 246 K | 1.4 GB |
| 433 | xlm-roberta-large-ner-hrl | 560 M | 512 | ✓ afl-3.0 | 246 K | 3.0 GB |
| 434 | plant-identity | 90 M | — | unknown | 245 K | 0.9 GB |
| 435 | Meta-Llama-3.1-8B-Instruct-AWQ-INT4 | 8.0 B | 131 K | ⚠ llama3.1 | 245 K | 8.0 GB |
| 436 | SmolLM2-1.7B | 1.7 B | 8 K | ✓ apache-2.0 | 243 K | 4.5 GB |
| 437 | h2ovl-mississippi-800m | 830 M | — | ✓ apache-2.0 | 242 K | 2.4 GB |
| 438 | NVIDIA-Nemotron-3.5-Lightning-30B-A3B-NVFP4-DSpark | 760 M | 1.0 M | other | 241 K | 2.1 GB |
| 439 | convnext_femto.d1_in1k | 10 M | — | ✓ apache-2.0 | 241 K | 0.5 GB |
| 440 | pythia-410m | 510 M | 2 K | ✓ apache-2.0 | 241 K | 1.6 GB |
| 441 | TinyStories-1M | 1.0 M | 2 K | unknown | 232 K | 0.5 GB |
| 442 | h2ovl-mississippi-2b | 2.2 B | — | ✓ apache-2.0 | 230 K | 5.6 GB |
| 443 | Agents-A1-4B-Q8_0-GGUF | — | — | ✓ apache-2.0 | 230 K | 1.2 GB |
| 444 | Qwen3-0.6B-GGUF | 600 M | 41 K | ✓ apache-2.0 | 229 K | 1.3 GB |
| 445 | Mistral-7B-Instruct-v0.3-AWQ | 7.3 B | 33 K | ✓ apache-2.0 | 229 K | 6.2 GB |
| 446 | Yi-Coder-9B-Chat-GGUF | — | — | unknown | 227 K | 2.7 GB |
| 447 | Ornith-1.5-9B-MLX-6bit | 9.0 B | — | unknown | 226 K | 9.8 GB |
| 448 | Llama-3.2-3B-Instruct-GGUF | — | 131 K | ⚠ llama3.2 | 224 K | 2.0 GB |
| 449 | Qwen2.5-1.5B-Instruct-GGUF | — | — | ✓ apache-2.0 | 224 K | 1.3 GB |
| 450 | Qwen-Image-2512-GGUF | — | — | ✓ apache-2.0 | 222 K | 8.6 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.