1,000 models · refreshed nightly
Models that run on RTX 4070 · 16 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 4070 · 16 GB |
|---|---|---|---|---|---|---|
| 401 | gpt2-medium | 380 M | — | ✓ mit | 317 K | 2.2 GB |
| 402 | xflux_text_encoders | 4.8 B | — | ✓ apache-2.0 | 317 K | 11.7 GB |
| 403 | table-transformer-structure-recognition-v1.1-all | 30 M | — | ✓ mit | 314 K | 0.6 GB |
| 404 | The_GuageLLM_23M | 20 M | — | ✓ apache-2.0 | 314 K | 0.6 GB |
| 405 | rubert-tiny-toxicity | 10 M | 512 | ✓ mit | 313 K | 0.6 GB |
| 406 | phishing-email-detection-distilbert_v2.4.1 | 70 M | 512 | ✓ apache-2.0 | 309 K | 0.8 GB |
| 407 | opt-350m | 350 M | 2 K | other | 308 K | 1.3 GB |
| 408 | llmlingua-2-bert-base-multilingual-cased-meetingbank | 180 M | 512 | ✓ apache-2.0 | 307 K | 1.3 GB |
| 409 | gpt-j-6b | 6.0 B | — | ✓ apache-2.0 | 304 K | 14.6 GB |
| 410 | SmolLM2-360M-Instruct | 360 M | 8 K | ✓ apache-2.0 | 303 K | 1.4 GB |
| 411 | Qwen2-0.5B-Instruct | 490 M | 33 K | ✓ apache-2.0 | 302 K | 1.7 GB |
| 412 | prokbert-mini-promoter | 20 M | 1 K | ✗ cc-by-nc-4.0 | 302 K | 0.6 GB |
| 413 | Qwen2.5-14B-bnb-4bit | 15.2 B | 131 K | ✓ apache-2.0 | 298 K | 13.7 GB |
| 414 | Qwen3.5-4B-Claude-4.6-Opus-Reasoning-Distilled-GGUF | — | — | ✓ apache-2.0 | 297 K | 2.5 GB |
| 415 | Qwopus-GLM-18B-Merged-GGUF | — | — | ✓ apache-2.0 | 295 K | 9.2 GB |
| 416 | Qwen3-0.6B-GGUF | — | — | unknown | 295 K | 0.9 GB |
| 417 | mask2former-swin-large-ade-semantic | 220 M | — | other | 295 K | 1.5 GB |
| 418 | DeepSeek-R1-0528-Qwen3-8B-MLX-4bit | 1.3 B | 131 K | ✓ mit | 293 K | 5.8 GB |
| 419 | nllb-200-distilled-1.3B | 1.3 B | 1 K | ✗ cc-by-nc-4.0 | 292 K | 3.6 GB |
| 420 | voice-gender-classifier | 20 M | — | ✓ mit | 291 K | 0.6 GB |
| 421 | KoELECTRA-small-v3-modu-ner | 10 M | 512 | unknown | 288 K | 0.6 GB |
| 422 | Qwen2.5-3B-Instruct-GGUF | — | — | other | 286 K | 2.0 GB |
| 423 | Qwen3.8-Flash-Next-GGUF | — | — | other | 285 K | 1.5 GB |
| 424 | Jan-v3.5-4B-gguf | — | — | ✓ apache-2.0 | 284 K | 2.8 GB |
| 425 | Llama-3.2-1B-Instruct-FP8-dynamic | 1.5 B | 131 K | ⚠ llama3.2 | 283 K | 3.0 GB |
| 426 | Ornith-1.5-9B-MLX-4bit | 9.0 B | — | unknown | 283 K | 7.4 GB |
| 427 | mamba-130m-hf | 130 M | — | unknown | 281 K | 1.1 GB |
| 428 | Flux2-Klein-9B-True-V2 | — | — | other | 281 K | 6.8 GB |
| 429 | vit_base_patch8_224.augreg2_in21k_ft_in1k | 90 M | — | ✓ apache-2.0 | 281 K | 0.9 GB |
| 430 | Llama-3.2-3B-Instruct-FP8-dynamic | 3.6 B | 131 K | ⚠ llama3.2 | 277 K | 5.9 GB |
| 431 | MuQ-large-msd-iter | 330 M | — | ✗ cc-by-nc-4.0 | 277 K | 2.0 GB |
| 432 | vit-age-classifier | 90 M | — | unknown | 275 K | 0.9 GB |
| 433 | MiniCPM5-2B-DSpark | 324 M | 131 K | ✓ apache-2.0 | 275 K | 1.3 GB |
| 434 | Qwen3-14B-GGUF | — | — | unknown | 274 K | 6.8 GB |
| 435 | gemma-4-31B-it-scotoma-2-GGUF | — | — | ✓ apache-2.0 | 274 K | 13.8 GB |
| 436 | vit_tiny_r_s16_p8_224.augreg_in21k | 10 M | — | ✓ apache-2.0 | 274 K | 0.5 GB |
| 437 | Qwen3-4B-GGUF | — | — | unknown | 272 K | 2.3 GB |
| 438 | tiny_starcoder_py | 160 M | — | bigcode-openrail-m | 272 K | 1.2 GB |
| 439 | Qwen2.5-Coder-7B-Instruct-GGUF | — | — | ✓ apache-2.0 | 272 K | 3.8 GB |
| 440 | DeepSeek-R1-0528-Qwen3-8B-MLX-8bit | 2.3 B | 131 K | ✓ mit | 271 K | 10.4 GB |
| 441 | CodonTransformer | 90 M | 4 K | ✓ apache-2.0 | 270 K | 0.9 GB |
| 442 | Qwen3-1.7B-GGUF | — | — | unknown | 270 K | 1.5 GB |
| 443 | Qwen3-0.6B-FP8 | 750 M | 41 K | ✓ apache-2.0 | 270 K | 1.8 GB |
| 444 | FLUX.1-dev-gguf | — | — | other | 269 K | 4.9 GB |
| 445 | Qwen3-8B-GGUF | — | — | unknown | 269 K | 4.1 GB |
| 446 | Qwen3-4B-AWQ | 4.0 B | 41 K | ✓ apache-2.0 | 268 K | 4.0 GB |
| 447 | taardis-27b-full-ternary | — | — | ✓ apache-2.0 | 268 K | 8.4 GB |
| 448 | Qwen3-30B-A3B-GGUF | — | — | unknown | 266 K | 12.9 GB |
| 449 | Qwen3-32B-GGUF | — | — | unknown | 266 K | 14.1 GB |
| 450 | openai-gpt | 120 M | — | ✓ mit | 265 K | 1.0 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API.