1,423 models · 1,213 open weights · 210 API-only · refreshed nightly
Models that run on RTX 4090 · 24 GB
Every model in the catalog — open weights you can self-host and API-only models — with licence or API price, estimated VRAM and daily-tracked downloads. Filters update the URL — share any view.
| # | Model | Params | Context | Commercial use | 30d | On RTX 4090 · 24 GB |
|---|---|---|---|---|---|---|
| 501 | Qwen3-30B-A3B-GGUF | — | — | ✓ apache-2.0 | 265 K | 20.9 GB |
| 502 | Ornith-1.5-9B-MLX-4bit | 9.0 B | — | unknown | 265 K | 7.4 GB |
| 503 | Qwen2.5-Coder-7B-Instruct-4bit | 1.2 B | 33 K | ✓ apache-2.0 | 264 K | 5.4 GB |
| 504 | phishing-distilbert-cyber207 | 67 M | 512 | unknown | 264 K | 0.8 GB |
| 505 | segformer-b0-finetuned-ade-512-512 | <0.1 M | — | unknown | 263 K | — |
| 506 | densenetblur121d.ra_in1k | 8.1 M | — | ✓ apache-2.0 | 262 K | 0.5 GB |
| 507 | TwIL-LM3 | 3.1 B | 66 K | other | 260 K | 3.1 GB |
| 508 | Qwen-Image-2.1-Turbo-GGUF | — | — | other | 259 K | 3.3 GB |
| 509 | waiIllustriousSDXL_v170 | — | — | cdla-permissive-2.0 | 259 K | 8.1 GB |
| 510 | rubert-tiny-toxicity | 10 M | 512 | ✓ mit | 258 K | 0.6 GB |
| 511 | LFM2.5-1.2B-Instruct-GGUF | 1.2 B | 128 K | other | 257 K | 1.4 GB |
| 512 | Kwaipilot_KAT-Coder-V2.5-Dev-GGUF | — | — | ✓ apache-2.0 | 257 K | 11.3 GB |
| 513 | shieldgemma-9b | 9.2 B | — | ⚠ gemma | 256 K | 22.2 GB |
| 514 | RMBG-1.4 | 40 M | — | other | 256 K | 0.7 GB |
| 515 | Llama-3.2-3B-Instruct-GGUF | — | 131 K | ⚠ llama3.2 | 253 K | 2.0 GB |
| 516 | Qwen2.5-1.5B-apeach | 1.5 B | 131 K | unknown | 251 K | 7.5 GB |
| 517 | Spark-X2.5-1.7B-GGUF | 1.7 B | — | ✓ apache-2.0 | 251 K | 2.0 GB |
| 518 | Ling-3.0-tiny-GGUF | — | 131 K | ✓ mit | 248 K | 2.4 GB |
| 519 | Z-Image-Turbo-GGUF | — | — | ✓ apache-2.0 | 247 K | 3.4 GB |
| 520 | FLUX.1-dev-gguf | — | — | other | 247 K | 4.9 GB |
| 521 | xlm-roberta-large-ner-hrl | 560 M | 512 | ✓ afl-3.0 | 246 K | 3.0 GB |
| 522 | indictrans2-en-indic-dist-200M | 275 M | — | ✓ mit | 244 K | 1.7 GB |
| 523 | h2ovl-mississippi-800m | 830 M | — | ✓ apache-2.0 | 242 K | 2.4 GB |
| 524 | cryptobert | 120 M | 512 | ✓ mit | 241 K | 1.1 GB |
| 525 | gliner_large-v2 | 460 M | — | ✓ apache-2.0 | 240 K | 2.6 GB |
| 526 | Qwen3-8B-FP8 | 8.2 B | 41 K | ✓ apache-2.0 | 240 K | 12.1 GB |
| 527 | Phi-3-mini-128k-instruct | 3.8 B | 131 K | ✓ mit | 239 K | 9.5 GB |
| 528 | s1-mini-GGUF | — | — | other | 239 K | 1.0 GB |
| 529 | Qwen2-0.5B-Instruct | 490 M | 33 K | ✓ apache-2.0 | 238 K | 1.7 GB |
| 530 | Llama-3.1-8B-Instruct | 8.0 B | 131 K | ⚠ llama3.1 | 238 K | 19.4 GB |
| 531 | gemma-3-270m | 270 M | — | ⚠ gemma | 238 K | 1.1 GB |
| 532 | SmolLM-135M-Instruct-FP32 | 135 M | 2 K | unknown | 238 K | 1.1 GB |
| 533 | MiniCPM5-1B | 1.1 B | 131 K | ✓ apache-2.0 | 236 K | 3.0 GB |
| 534 | nsfw-classifier | 90 M | — | ✗ cc-by-nc-nd-4.0 | 236 K | 0.9 GB |
| 535 | POCKET-26B-GGUF | 26.0 B | — | ✓ apache-2.0 | 234 K | 16.6 GB |
| 536 | rtdetr_r50vd | 40 M | — | ✓ apache-2.0 | 234 K | 0.7 GB |
| 537 | roberta-large-mnli | 360 M | 512 | ✓ mit | 234 K | 2.1 GB |
| 538 | Llama-3.2-3B-Instruct-FP8-dynamic | 3.6 B | 131 K | ⚠ llama3.2 | 233 K | 5.9 GB |
| 539 | granite-3.3-2b-instruct | 2.5 B | 131 K | ✓ apache-2.0 | 233 K | 6.5 GB |
| 540 | diffusiongemma-26B-A4B-it-NVFP4 | 14.4 B | — | ✓ apache-2.0 | 232 K | 23.4 GB |
| 541 | resnet18.a3_in1k | 10 M | — | ✓ apache-2.0 | 231 K | 0.6 GB |
| 542 | t5-3b | 2.9 B | — | ✓ apache-2.0 | 230 K | 13.5 GB |
| 543 | t5-large | 740 M | — | ✓ apache-2.0 | 230 K | 3.9 GB |
| 544 | h2ovl-mississippi-2b | 2.2 B | — | ✓ apache-2.0 | 230 K | 5.6 GB |
| 545 | stable-diffusion-inpainting | — | — | ⚠ creativeml-openrail-m | 229 K | 3.5 GB |
| 546 | h2o-danube3-500m-chat | 514 M | 8 K | ✓ apache-2.0 | 229 K | 1.7 GB |
| 547 | Llama-3.1-8B-Instruct-4bit | 1.3 B | 131 K | ⚠ llama3.1 | 228 K | 5.7 GB |
| 548 | ftrobertallm | 355 M | 512 | ✓ mit | 225 K | 2.1 GB |
| 549 | prompt-saturation-attack-detector | 4.4 M | 512 | unknown | 225 K | 0.5 GB |
| 550 | Qwen3-8B-FP8 | 8.2 B | 41 K | ✓ apache-2.0 | 225 K | 12.1 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.