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 |
|---|---|---|---|---|---|---|
| 351 | DeepSeek-R1-0528-Qwen3-8B-MLX-8bit | 2.3 B | 131 K | ✓ mit | 258 K | 10.4 GB |
| 352 | plant-identity | 90 M | — | unknown | 257 K | 0.9 GB |
| 353 | bert-base-multilingual-cased-ner-hrl | 180 M | 512 | ✓ afl-3.0 | 249 K | 1.3 GB |
| 354 | span-marker-bert-base-uncased-acronyms | 110 M | — | ✓ apache-2.0 | 247 K | 1.0 GB |
| 355 | Bielik-11B-v3.0-Instruct-awq | 11.3 B | 33 K | ✓ apache-2.0 | 247 K | 9.0 GB |
| 356 | xlm-roberta-large-ner-hrl | 560 M | 512 | ✓ afl-3.0 | 246 K | 3.0 GB |
| 357 | wav2vec2-large-robust-24-ft-age-gender | 320 M | — | ✗ cc-by-nc-sa-4.0 | 246 K | 1.9 GB |
| 358 | pythia-410m | 510 M | 2 K | ✓ apache-2.0 | 244 K | 1.6 GB |
| 359 | llama-160m | 160 M | 2 K | ✓ apache-2.0 | 243 K | 1.2 GB |
| 360 | hubert-large-speech-emotion-recognition-russian-dusha-finetuned | 320 M | — | ✓ apache-2.0 | 243 K | 1.9 GB |
| 361 | Phi-3-mini-128k-instruct | 3.8 B | 131 K | ✓ mit | 242 K | 9.5 GB |
| 362 | ai-image-detector-dev-deploy | 200 M | — | unknown | 241 K | 2.2 GB |
| 363 | table-transformer-structure-recognition-v1.1-all | 30 M | — | ✓ mit | 240 K | 0.6 GB |
| 364 | Qwen3-8B-GGUF | — | — | ✓ apache-2.0 | 239 K | 6.0 GB |
| 365 | tiny_starcoder_py | 160 M | — | bigcode-openrail-m | 238 K | 1.2 GB |
| 366 | Qwen2.5-3B-Instruct-AWQ | 3.4 B | 33 K | other | 238 K | 4.0 GB |
| 367 | pythia-14m | 10 M | 2 K | ✓ apache-2.0 | 237 K | 0.5 GB |
| 368 | internlm2-1_8b-reward | 1.7 B | 33 K | other | 236 K | 4.5 GB |
| 369 | convnext_base.fb_in22k_ft_in1k | 90 M | — | ✓ apache-2.0 | 236 K | 0.9 GB |
| 370 | layoutreader | 360 M | 514 | ✗ cc-by-nc-sa-4.0 | 234 K | 1.3 GB |
| 371 | gliner_multi-v2.1 | 290 M | — | ✓ apache-2.0 | 234 K | 1.8 GB |
| 372 | Llama-3.2-1B-Instruct-Q8_0-GGUF | — | — | unknown | 233 K | 2.0 GB |
| 373 | distilbert-NER | 70 M | 512 | ✓ apache-2.0 | 231 K | 0.8 GB |
| 374 | Phi-3-vision-128k-instruct | 4.2 B | 131 K | ✓ mit | 231 K | 10.2 GB |
| 375 | TinyLLama-v0 | 0 M | 2 K | ✓ apache-2.0 | 226 K | 0.5 GB |
| 376 | LFM2.5-1.2B-Instruct-GGUF | — | — | other | 226 K | 1.3 GB |
| 377 | Qwen3.6-35B-A3B-DFlash | 390 M | 262 K | ✓ apache-2.0 | 224 K | 1.4 GB |
| 378 | Qwen3-4B-GGUF | — | — | unknown | 223 K | 2.3 GB |
| 379 | vlt5-base-keywords | 280 M | — | ✓ cc-by-4.0 | 223 K | 1.8 GB |
| 380 | gemma-4-12b-heretic-abliterated-GGUF | — | — | ✓ apache-2.0 | 219 K | 0.7 GB |
| 381 | Meta-Llama-3.1-8B-FP8 | 8.0 B | 131 K | ⚠ llama3.1 | 216 K | 11.7 GB |
| 382 | dvine82-xl | 2.6 B | — | unknown | 213 K | 8.5 GB |
| 383 | SmolLM2-1.7B-Instruct | 1.7 B | 8 K | ✓ apache-2.0 | 213 K | 4.5 GB |
| 384 | Mistral-7B-Instruct-v0.3-AWQ | 7.3 B | 33 K | ✓ apache-2.0 | 212 K | 6.2 GB |
| 385 | IP-Adapter-FaceID | — | — | unknown | 210 K | 1.5 GB |
| 386 | t5-large | 740 M | — | ✓ apache-2.0 | 210 K | 3.9 GB |
| 387 | xflux_text_encoders | 4.8 B | — | ✓ apache-2.0 | 203 K | 11.7 GB |
| 388 | Qwen2.5-Coder-1.5B | 1.5 B | 33 K | ✓ apache-2.0 | 200 K | 4.1 GB |
| 389 | gemma-1.1-2b-it | 2.5 B | — | ⚠ gemma | 200 K | 6.4 GB |
| 390 | Qwen2.5-1.5B-Instruct-GGUF | — | — | ✓ apache-2.0 | 199 K | 1.3 GB |
| 391 | Qwen1.5-0.5B-Chat | 620 M | 33 K | other | 199 K | 2.0 GB |
| 392 | aya-expanse-8b-AWQ | 9.1 B | 8 K | gpl-3.0 | 198 K | 10.5 GB |
| 393 | Qwen3-4B-Thinking-2507-FP8 | 4.4 B | 262 K | ✓ apache-2.0 | 197 K | 6.9 GB |
| 394 | Qwen2.5-Coder-32B-Instruct-GGUF | — | — | ✓ apache-2.0 | 197 K | 9.1 GB |
| 395 | pythia-160m-deduped | 210 M | 2 K | ✓ apache-2.0 | 191 K | 0.9 GB |
| 396 | Qwen2.5-Coder-7B-Instruct-GGUF | — | — | ✓ apache-2.0 | 189 K | 3.8 GB |
| 397 | Llama-3.2-3B-Instruct | 3.2 B | 131 K | ⚠ llama3.2 | 188 K | 8.0 GB |
| 398 | Qwen3-0.6B-GGUF | — | — | unknown | 186 K | 0.9 GB |
| 399 | Sugoi-14B-Ultra-GGUF | — | — | ✓ apache-2.0 | 185 K | 6.8 GB |
| 400 | Qwen2.5-3B-Instruct-GGUF | — | — | other | 185 K | 2.0 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.