1,213 models · 1,213 open weights · 210 API-only · refreshed nightly
Open-weights models
Models whose weights are published on Hugging Face — download them and run them on your own hardware. Many are also served by hosted providers; those carry an "Also via API" badge with live prices.
| # | Model | Params | Context | Commercial use | 30d | On RTX 4090 · 24 GB |
|---|---|---|---|---|---|---|
| 351 | Sage-A1.5-Q8_0-GGUF | — | — | ✓ apache-2.0 | 490 K | 1.5 GB |
| 352 | Qwen3-Coder-30B-A3B-Instruct-GGUF | — | — | ✓ apache-2.0 | 486 K | 12.9 GB |
| 353 | Voxtral-Mini-4B-Realtime-2602-gguf | 4.0 B | — | ✓ apache-2.0 | 485 K | 4.2 GB |
| 354 | stable-diffusion-v1-4 | 860 M | — | ⚠ creativeml-openrail-m | 483 K | 13.5 GB |
| 355 | Qwen2.5-Coder-7B-Instruct-GPTQ-Int4 | 7.6 B | 33 K | ✓ apache-2.0 | 482 K | 7.8 GB |
| 356 | Qwen3.8-27B-DFlash2-GGUF | — | — | ✓ apache-2.0 | 481 K | 1.8 GB |
| 357 | NVIDIA-Nemotron-3.5-Bolt-E4B-GGUF | 4.0 B | — | other | 481 K | 5.0 GB |
| 358 | Llama-3.2-1B | 1.2 B | — | ⚠ llama3.2 | 477 K | 3.4 GB |
| 359 | embeddinggemma-2 | 744 M | — | ✓ apache-2.0 | 475 K | 2.2 GB |
| 360 | Llama-3.1-8B | 8.0 B | — | ⚠ llama3.1 | 475 K | 19.4 GB |
| 361 | sentence-bert-base-ja-mean-tokens-v2 | 110 M | 512 | cc-by-sa-4.0 | 474 K | 1.0 GB |
| 362 | llama-3-8b-Instruct-bnb-4bit | 8.2 B | 8 K | ⚠ llama3 | 472 K | 8.0 GB |
| 363 | wav2vec2-large-xlsr-japanese-hiragana | 320 M | — | ✓ apache-2.0 | 472 K | 1.9 GB |
| 364 | nli-mpnet-base-v2 | 110 M | 512 | ✓ apache-2.0 | 472 K | 1.0 GB |
| 365 | bge-small-en-v1.5 | 33 M | 512 | ✓ mit | 470 K | 0.7 GB |
| 366 | Qwen2.5-7B | 7.6 B | 131 K | ✓ apache-2.0 | 469 K | 18.4 GB |
| 367 | JiRackDeltaNet_27b | 27.3 B | 262 K | ✓ mit | 468 K | 16.5 GB |
| 368 | wav2vec2-large-xlsr-kazakh | 320 M | — | ✓ apache-2.0 | 466 K | 1.9 GB |
| 369 | pplx-embed-v1-0.6b | 600 M | 33 K | ✓ mit | 461 K | 3.2 GB |
| 370 | rubert-tiny2 | 30 M | 2 K | ✓ mit | 460 K | 0.6 GB |
| 371 | nsfw_image_detector | 90 M | — | ✓ mit | 460 K | 0.7 GB |
| 372 | sat-3l-sm | 210 M | 514 | ✓ mit | 460 K | 1.5 GB |
| 373 | robertuito-sentiment-analysis | 110 M | 128 | unknown | 459 K | 1.0 GB |
| 374 | gpt-neo-125m | 150 M | 2 K | ✓ mit | 458 K | 1.1 GB |
| 375 | mimi | 100 M | 8 K | ✓ cc-by-4.0 | 458 K | 0.9 GB |
| 376 | multilingual-e5-small | 120 M | 512 | unknown | 456 K | 0.8 GB |
| 377 | MedCPT-Query-Encoder | 110 M | 512 | other | 454 K | 1.0 GB |
| 378 | sd-turbo | 870 M | — | unknown | 454 K | 14.9 GB |
| 379 | open-vakgyata | 60 M | — | ✗ cc-by-nc-4.0 | 453 K | 0.8 GB |
| 380 | gte-base-en-v1.5 | 137 M | 8 K | ✓ apache-2.0 | 452 K | 1.1 GB |
| 381 | Qwen3-4B-Base | 4.0 B | 33 K | ✓ apache-2.0 | 447 K | 10.0 GB |
| 382 | Mellum2.1-12B-A2.5B-Thinking-GGUF | 12.0 B | — | ✓ apache-2.0 | 446 K | 11.5 GB |
| 383 | MiniCPM5-2B-GGUF | 2.0 B | — | ✓ apache-2.0 | 446 K | 2.5 GB |
| 384 | Qwen2.5-Coder-3B-Instruct | 3.1 B | 33 K | other | 441 K | 7.8 GB |
| 385 | sqlcoder-7b-2 | 6.7 B | 16 K | cc-by-sa-4.0 | 441 K | 6.8 GB |
| 386 | nllb-200-distilled-1.3B | 1.3 B | 1 K | ✗ cc-by-nc-4.0 | 440 K | 3.6 GB |
| 387 | Qwen2.5-0.5B-Instruct-GGUF | — | — | ✓ apache-2.0 | 440 K | 1.0 GB |
| 388 | Apodex-1.1-mini-GGUF | — | — | ✓ apache-2.0 | 439 K | 10.2 GB |
| 389 | S-PubMedBert-MedQuAD | 110 M | 512 | ✓ mit | 439 K | 1.0 GB |
| 390 | Qwen3.8-27B-DFlash2 | 1.9 B | 262 K | ✓ apache-2.0 | 438 K | 5.0 GB |
| 391 | clipseg-rd64-refined | 150 M | — | ✓ apache-2.0 | 437 K | 1.2 GB |
| 392 | Qwen-Image-2.1-Lightning | 7.1 B | — | unknown | 436 K | 1.6 GB |
| 393 | segformer_b2_clothes | 30 M | — | other | 434 K | 0.6 GB |
| 394 | vram-16 | — | — | unknown | 432 K | 0.5 GB |
| 395 | LFM2.5-24B-A2B-GGUF | 24.0 B | 131 K | other | 430 K | 12.3 GB |
| 396 | lambda | — | — | unknown | 428 K | 0.5 GB |
| 397 | efficient-splade-VI-BT-large-doc | — | 512 | ✗ cc-by-nc-sa-4.0 | 427 K | 0.5 GB |
| 398 | Qwen3-14B-GGUF | — | — | ✓ apache-2.0 | 424 K | 10.4 GB |
| 399 | maple-preview-GGUF | — | — | ✓ mit | 424 K | 6.5 GB |
| 400 | Meta-Llama-3-8B-Instruct-abliterated-v3 | 8.0 B | 8 K | ⚠ llama3 | 420 K | 19.4 GB |
VRAM figures are estimates for the smallest available quantization at 8K context — see /methodology. Downloads refresh nightly from the Hugging Face API; API prices (blended 3:1 input:output per 1M tokens) and Artificial Analysis indices from OpenRouter.